Search Results (99)

Since the first paper published by Susan Cole in 1990 detailing multidrug resistance mediated by ABCC1/MRP1, research into the C-subfamily of ATP-binding cassette transporters has continued to uncover a wide range of functionally divergent proteins. However, several orphan transporters remain in the C-subfamily, and the physiological function and substrates of ABCC5, ABCC11, and ABCC12 remain elusive. This review explores the emerging understanding of human ABCC5. Unlike other ABC transporters with well-defined drug export functions, ABCC5’s physiological roles remain only partially understood. While it is known for its involvement in multidrug resistance in cancers, recent studies suggest broader implications in development, metabolism, neurobiology, and male fertility. ABCC5 exports various endogenous substrates, including cyclic nucleotides (cAMP and cGMP), glutamate conjugates like NAAG, and possibly haem. Knockout models in mice, zebrafish, and sea urchins reveal ABCC5’s role in gut formation, brain function, eye development, and iron metabolism. In mice, its deletion results in lower adipose tissue mass, enhanced insulin sensitivity, and neurobehavioral changes resembling schizophrenia, highlighting its role in glutamatergic signalling and circadian regulation. Functionally, ABCC5 appears to impact adipocyte differentiation and GLP-1 release, implicating it in type 2 diabetes susceptibility in humans. Structural studies using human ABCC5 revealed a novel autoinhibitory mechanism involving a peptide segment (C46–S64) that blocks substrate binding, offering new potential for selective inhibitor development. However, this review emphasises caution in targeting ABCC5 for cancer therapy due to its underappreciated physiological function(s), particularly in the brain and male reproductive system. Understanding ABCC5’s substrate specificity, regulatory mechanisms, and functional redundancy with its paralog ABCC12 remains critical for successful therapeutic strategies in humans. Full article

Soil nutrient monitoring is essential to achieving UN development goals and meeting the projected 70% increase in agricultural production from 2009 values by 2050. This study presents a novel, low-cost impedimetric device for the direct and simultaneous measurement of soil ion bioavailability (Na⁺, K⁺), temperature, and humidity. Designed for Arduino integration, the device offers scalable, cost-effective deployment. Different AI algorithms were trained to interpret signals (Support Vector Machine, Random Forest, XBoost), enabling real-time monitoring. Best performance was achieved for XBoost. Calibration was first performed using solutions of known NaCl and KCl concentrations to establish impedance patterns, and benchmarking against fitted Cole model outputs demonstrated high predictive accuracy (R² = 0.99 for both Na⁺ and K⁺). The system operated across a 1–100 kHz impedance range with environmental resolution of ±0.5 °C, ±3% RH, and ±1 hPa, acquiring data every 10 min during in vivo trials. This affordable, AI-enhanced platform has the potential to empower smallholder farmers by reducing reliance on costly laboratory analyses, enabling precise fertiliser application, and integrating seamlessly into smart farming platforms for sustainable yield improvement. Full article

Jordan’s aging population faces a critical challenge: a strong cultural preference for aging at home, rooted in Islamic ethics of familial care (birr al-wālidayn), conflicts with housing stock that is largely unsafe and inaccessible. This first national mixed-methods study examines the intersection of home modifications, socio-economic barriers, and cultural constraints to aging in place. Data from 587 surveys and 35 interviews across seven governorates were analyzed using chi-square tests, linear regression, and thematic coding. Results indicate that while physical modifications significantly improve accessibility to key spaces like kitchens and reception areas (majlis) (χ² = 341.86, p < 0.001), their adoption is severely limited. Socio-economic barriers are paramount, with 34% of households unable to afford the median modification cost of over $1500. Cultural resistance is equally critical; 22% of widows avoid modifications like grab bars to prevent the ‘medicalization’ of their home, prioritizing aesthetic and symbolic integrity over safety. The study reveals a significant gendered decision-making dynamic, with men controlling 72% of structural modifications (β = 0.27, p < 0.001). We conclude that effective policy must integrate universal design with Islamic care ethics. We propose three actionable recommendations: (1) mandating universal design in building codes (aligned with SDG 11), (2) establishing means-tested subsidy programs (aligned with SDG 10), and (3) launching public awareness campaigns co-led by faith leaders to reframe modifications as preserving dignity (karama) (aligned with SDG 3). This approach provides a model for other rapidly aging Middle Eastern societies facing similar cultural-infrastructural tensions. Full article

Background: Early identification of visual disorders in children is essential to prevent long-term visual impairment and support academic development. Despite the recognized importance of visual screenings, no universal consensus exists on which visual parameters or threshold values should be used, particularly for measuring visual acuity (VA) in pediatric populations. Objectives: This study aimed to develop age-related percentile norms for VA using LEA symbol charts. Methods: A sample of Italian schoolchildren aged 5 to 15 years (n = 1510) participated in the study. Data were collected retrospectively from school-based vision screenings conducted across 12 schools in the Lombardy and Piedmont regions from 2010 to 2019. Monocular and binocular VA were measured at 3 m using a standardized LEA symbol chart, and values were scored letter-by-letter on a LogMAR scale. Smoothed percentile curves were derived using Box–Cox, Cole, and Green distribution modeling and regression analysis. Results: The results showed a non-linear improvement in VA with age. Compared to prior studies, LEA symbols yielded slightly lower VA scores, reinforcing the need for chart-specific norms. The 50th percentile VA improved from approximately +0.07 LogMAR at age 6 to about −0.09 LogMAR at age 15. Conclusions: These findings highlight the importance of age-specific, chart-specific, and statistically robust reference data for VA screening in children. The derived percentile tables offer a more sensitive tool than fixed cut-offs for identifying visual anomalies and tailoring clinical interventions. This work contributes to standardizing pediatric VA screening practices and improving early detection of visual deficits. Full article

The frequency-domain controlled-source electromagnetic method (CSEM) has been widely used in fields such as oil and gas and mineral resource exploration. In areas with a significant IP response, the CSEM signals will be modified by the IP response of the subsurface. Accurately extracting resistivity and polarization information from CSEM signals may significantly improve the exploration interpretations. In this study, we replaced real resistivity with the Cole–Cole complex resistivity model in a forward simulation of the CSEM to obtain electric field responses that included both induced polarization and electromagnetic effects. Based on this, we used the adaptive differential evolution algorithm to perform a 1-d inversion of these data to extract both the resistivity and IP parameters. Inversion of the electric field responses from representative three-layer geoelectric models, as well as from a more realistic seven-layer model, showed that the inversions were able to effectively recover resistivity and polarization information from the modeled responses, validating our methodology. The electric field response of the real geoelectric model, with 20% random noise added, was then used to simulate actual measured CSEM signals, as well as subjected to multiple inversion tests. The results of these tests continued to accurately reflect the resistivity and polarization information of the model, confirming the applicability and reliability of the algorithm. These results have significant implications for the processing and interpretation of CSEM data when induced polarization effects merit consideration and are expected to promote the use of the CSEM in more fields. Full article

Cell membrane capacitance (C_m) is a potential biomarker that reflects the structural and functional integrity of cell membranes. It is essential for physiological processes such as signal transduction, ion transport, and cellular homeostasis. In clinical practice, C_m can be determined using bioimpedance spectroscopy (BIS), a non-invasive technique for analysing the intrinsic electrical properties of biological tissues across a range of frequencies. C_m may be relevant in various clinical fields, where high capacitance is associated with healthy and intact membranes, while low capacitance indicates cellular damage or disease. Despite its promise as a prognostic indicator, several knowledge gaps limit the broader clinical application of C_m. These include variability in measurement techniques (e.g., electrode placement, frequency selection), the lack of standardised measurement protocols, uncertainty on how C_m is related to pathology, and the relatively low amount of C_m research. By addressing these gaps, C_m may become a valuable tool for examining cellular health, early disease detection, and evaluating treatment efficacy in clinical practice. This review explores the fundamental principles of C_m measured with the BIS technique, its mathematical basis and relationship to the biophysical Cole model, and its potential clinical applications. It identifies current gaps in our knowledge and outlines future research directions to enhance the understanding and use of C_m. For example, C_m has shown promise in identifying membrane degradation in sepsis, predicting malnutrition in anorexia nervosa, and as a prognostic factor in cancer. Full article

Gender inequality remains a persistent issue in healthcare, especially in ophthalmology, where women face systemic barriers such as pay gaps, limited surgical opportunities, harassment, and unequal family expectations. Despite increasing entry into the field, women remain underrepresented in leadership, affecting career advancement and patient care. This study examines how virtual platforms, and co-led initiatives can address gender disparities in eye health. In 2021, Women in Ophthalmology, Seva Foundation, and Orbis International launched the Women’s Leaders in Eye Health (WLEH) initiative—a global community promoting mentorship, networking, and leadership development. Starting with virtual webinars and informal networking, the initiative expanded to in-person events in 2023 due to strong global engagement and demand. Early virtual programming, including webinars and “Coffee Hour” sessions, proved effective and laid the groundwork for broader offerings such as mentorship and professional development grants. WLEH’s success underscores the power of collaboration in promoting gender equity. By fostering connections and leadership pathways, WLEH offers a scalable model to break down gender challenges and uplift the next generation of women leaders to deliver more accessible eyecare globally. Full article

To quantitatively describe the frequency domain spectroscopy (FDS) characteristics of transformer oil-paper insulation under varying temperature, moisture, and aging conditions, a modified Cole–Cole model is introduced. This model decomposes the dielectric spectrum into polarization, DC conduction, and hopping conduction components, with parameters reflecting insulation characteristics. Methods for determining initial parameter values and optimizing the objective function are proposed. Using a three-electrode setup, FDS measurements were conducted on oil-paper insulation samples at different temperatures, and extracted parameters were analyzed for their variation patterns. Within the frequency range of 1.98 × 10⁻⁴ Hz to 1 × 10³ Hz, the model achieves a goodness-of-fit (R²) exceeding 0.97 for both real and imaginary permittivity components, with the sum of squared errors reduced from 259 to 57.35 at 70 °C, outperforming the fundamental Cole–Cole and Ekanayake’s models. Temperature significantly affects the relaxation and DC conductivity components; both adhere to the Arrhenius equation, enabling precise condition assessment of transformer insulation. Full article

In knowledge graph construction, missing facts often lead to incomplete structures, thereby limiting the performance of downstream applications. Although recent knowledge graph completion (KGC) methods based on representation learning have achieved notable progress, they still suffer from two fundamental limitations, namely the lack of structured reasoning capabilities and the inability to assess the confidence of their predictions, which often results in unreliable outputs. We propose the GLR framework, which integrates Graph Chain-of-Thought (Graph-CoT) reasoning, LoRA fine-tuning, and the P(True)-based confidence evaluation mechanism. In the KGC task, this approach effectively enhances the reasoning ability and prediction reliability of large language models (LLMs). Specifically, Graph-CoT introduces local subgraph structures to guide LLMs in performing graph-constrained, step-wise reasoning, improving their ability to model multi-hop relational patterns. Complementing this, LoRA-based fine-tuning enables efficient adaptation of LLMs to the KGC scenario with minimal computational overhead, further enhancing the model’s capability for graph-structured reasoning. Moreover, the P(True) mechanism quantifies the reliability of candidate entities, improving the robustness of ranking and the controllability of outputs, thereby enhancing the credibility and interpretability of model predictions in knowledge reasoning tasks. We conducted systematic experiments on the standard KGC datasets FB15K-237, WN18RR, and UMLS, which demonstrate the effectiveness and robustness of the GLR framework. Notably, GLR achieves a Mean Reciprocal Rank (MRR) of 0.507 on FB15K-237, marking a 6.8% improvement over the best recent instruction-tuned method, DIFT combined with CoLE (MRR = 0.439). GLR also maintains significant performance advantages on WN18RR and UMLS, verifying its effectiveness in enhancing both the structured reasoning capabilities and the prediction reliability of LLMs for KGC tasks. These results indicate that GLR offers a unified and scalable solution to enhance structure-aware reasoning and output reliability of LLMs in KGC. Full article

The complex dielectric permittivity has been studied with the waves of millimeter wavelength for rare earth manganate and titanate and LiCoPO₄ and LiNi_0.5Co_0.5PO₄ orthophosphate composites. The measurements are carried out at frequencies of 26 to 38 GHz via measurements of transmission and reflection coefficients through a plate. A special method on how to extract the real and imaginary parts of dielectric permittivity is applied. Discussion is conducted on a nonmonotonic type of the frequency dependences for both real and imaginary parts of permittivity, and it has been shown that relaxation is non-Debye. The Cole–Cole, Havriliak–Negami, and Kohlrausch–Williams–Watts models cannot also explain the nonmonotonic frequency dependence of the real part of dielectric permittivity. Investigation of the structure and phase composition of nanocomposites has been carried out. Full article

Salt concentration monitoring is crucial for industrial process control and wastewater management, yet existing methods often lack real-time capability or require invasive sampling. This paper presents a novel RFID wireless sensing system for noninvasive solution concentration monitoring, combining physical modeling with advanced estimation algorithms. By combining the Cole–Cole model and the slit cylindrical capacitor (SCC) model, the system establishes physics-based state-space models to characterize concentration-dependent RFID signal variations. The concentration dynamics are modeled as a hidden Markov process and tracked using an adaptive extended Kalman filter (AEKF). The AEKF algorithm avoids computationally expensive inversion of complex observation equations while automatically adjusting noise covariance matrices via innovation sequence. Experimental results demonstrate a mean relative error (MRE) of 2.8% for CaCl₂ solution across 2–10 g/L concentrations. Within the experimentally validated optimal range (2–8 g/L CaCl₂), the system maintains MRE below 3% under artificially introduced measurement noise, confirming its strong robustness. Compared with baseline approaches, the proposed AEKF algorithm shows improved performance in both accuracy and computational efficiency. Full article

To investigate the dynamic mechanical properties of warm-mix steel slag-crumb rubber modified asphalt mixtures across wide- and narrow-frequency domains and evaluate the applicability of warm-mix technology, four distinct mixtures were prepared. The dynamic modulus characteristics under measured temperatures and frequencies were initially analyzed through complex modulus testing to elucidate narrow-frequency-domain mechanical behavior. Subsequently, leveraging the linear viscoelastic (LVE) theory and time–temperature superposition principle (TTSP), both the 2 Springs, 2 Parabolic Elements and 1 Dashpot (2S2P1D) mechanical element model and Modified Havriliak–Negami (MHN) mathematical model were established based on experimental data to characterize wide-frequency-domain dynamic responses. The results demonstrate substantial consistency in mechanical interpretation between narrow- and wide-frequency domain datasets, with enhanced information resolution achieved in wide-frequency analysis. Both models demonstrate comparable accuracy in characterizing the thermomechanical behavior of warm-mix steel slag-crumb rubber modified asphalt mixture across extended frequency and temperature ranges, while showing negligible performance discrepancies between the 2S2P1D and MHN formulations. Furthermore, both Cole–Cole and Black diagrams convincingly demonstrate the reliability of model predictions. This systematic investigation confirms the technical viability of warm-mix steel slag-crumb rubber modified asphalt mixture while establishing a dual-validated modeling framework for comprehensive performance prediction. Full article

Accurate parameter estimation is essential for effective monitoring and treatment of high-salinity industrial wastewater. Traditional methods such as spectroscopy, ion chromatography, and electrochemical analysis offer high sensitivity but are often complex, costly, and unsuitable for real-time monitoring. This research integrates Deep Neural Networks (DNNs) with the Levenberg–Marquardt (LM) algorithm to develop an advanced RFID-based sensing system for real-time monitoring of sodium chloride solutions in wastewater. The DNN extracts essential features from raw data, while the LM algorithm optimizes parameter estimation for enhanced precision and stability. Experimental results show that the dielectric constant sample variance at various flow rates under wireless frequency is 0.08509, while the sample total variance is 0.06807, both below 0.1. Additionally, the sample standard deviation and total standard deviation are both below 0.3, at 0.26090 and 0.29169, respectively. These findings confirm that the proposed system is robust against flow rate variations, ensuring accurate, real-time monitoring and supporting sustainable industrial practices. Full article

A mononuclear complex [Dy(phenN₆)(HL′)₂]PF₆·CH₂Cl₂ (H₂L′ = R/S-1,1′-binaphthyl-2,2′-diphenol) with local D_6h symmetry was synthesized. Structural determination shows that Dy³⁺ was encapsulated within the coordination cavity of the neutral hexaaza macrocyclic ligand phenN₆, forming a non-planar coordination environment. The axial positions are occupied by two phenoxy groups of binaphthol in the trans form. The local geometry of Dy³⁺ closely resembles a regular hexagonal bipyramid D_6h configuration. The axial Dy-O_phenoxy distances are 2.189(5) and 2.145(5) Å, respectively, while the Dy-N bond lengths in the equatorial plane are in the range of 2.524(7)–2.717(5) Å. The axial O_phthalmoxy-Dy-O_phthalmoxy bond angle is 162.91(17)°, which deviates from the ideal linearity. Under the excitation at 320 nm, the complex exhibits a characteristic emission peak at 360 nm, corresponding to the naphthalene ring. The AC susceptibility measurements under an applied DC field of 1800 Oe show distinct temperature-dependent and frequency-dependent AC magnetic susceptibility, typical of single-molecule magnetic behavior. The Cole–Cole plot in the temperature range of 6.0–28.0 K was fitted using a model incorporating Orbach and Raman relaxation mechanisms, giving an effective energy barrier of U_eff = 300.2 K. Theoretical calculations on complex 1 reveal that the magnetization relaxation proceeds through the first excited Kramers doublets with a calculated magnetization blocking barrier of 404.1 cm⁻¹ (581.4 K). Full article

This work presents an innovative bioimpedance spectroscopy device, developed as a support tool for decision-making during the evaluation of kidney viability for renal transplantation. Given the increasing demand for organs and the need to optimize donation criteria, the precise and objective assessment of renal graft functionality has become crucial. The device, based on a modular design and adapted to the surgical environment, uses a novel Cole model with a frequency-dependent membrane capacitance, which improves measurement accuracy and repeatability compared to conventional models. Adapting the device for operating room usege involved overcoming significant challenges, such as the need for sterilization and a visual, tactile and acoustic user interface that facilitates device usability. Optimizing the sensing stage has minimized the influence of measurement artifacts, which is crucial for obtaining accurate and representative measurements of renal tissue bioelectrical properties. In addition, a rigorous electrode sterilization protocol was designed, ensuring asepsis during the procedure. The results of tests on porcine renal models demonstrated the device’s ability to monitor pathophysiological changes associated with renal ischemia, with a notable improvement against measurement repeatability. Full article