Search Results (80)

As artificial intelligence systems increasingly govern public safety operations, concerns over algorithmic fairness and legal compliance intensify. This study introduces a scenario-based evaluation framework (SCRAM) that simultaneously measures regulatory conformity and bias risks in AI-enabled surveillance. Using license plate recognition (LPR) systems in Türkiye as a case study, we simulate multiple operational configurations that vary decision thresholds and data retention periods. Each configuration is assessed through fairness metrics (SPD, DIR) and a compliance score derived from KVKK (Türkiye’s Personal Data Protection Law) and constitutional jurisprudence. Our findings show that technical performance does not guarantee normative acceptability: several configurations with high detection accuracy fail to meet legal and fairness thresholds. The SCRAM model offers a modular and adaptable approach to align AI deployments with ethical and legal standards and highlights how policy-sensitive parameters critically shape risk landscapes. We conclude with implications for real-time audit systems and cross-jurisdictional AI governance. Full article

Inelastic electron tunneling spectroscopy (IETS) has emerged as a powerful vibrational spectroscopy technique for molecular electronic junctions, providing unique insights into molecular vibrations and electron–phonon coupling at the nanoscale. In this review, we present a comprehensive overview of IETS in molecular junctions, tracing its development from foundational principles to the latest advances. We begin with the theoretical background, detailing the mechanisms by which inelastic tunneling processes generate vibrational fingerprints of molecules, and highlighting how IETS complements optical spectroscopies by accessing electrically driven vibrational excitations. We then discuss recent progress in experimental techniques and device architectures that have broadened the applicability of IETS. Central focus is given to emerging applications of IETS over the last decade: molecular sensing (identification of chemical bonds and conformational changes in junctions), thermoelectric energy conversion (probing vibrational contributions to molecular thermopower), molecular switches and functional devices (monitoring bias-driven molecular state changes via vibrational signatures), spintronic molecular junctions (detecting spin excitations and spin–vibration interplay), and advanced data analysis approaches such as machine learning for interpreting complex tunneling spectra. Finally, we discuss current challenges, including sensitivity at room temperature, spectral interpretation, and integration into practical devices. This review aims to serve as a thorough reference for researchers in physics, chemistry, and materials science, consolidating state-of-the-art understanding of IETS in molecular junctions and its growing role in molecular-scale device characterization. Full article

Background/Objectives: Tegoprazan (TPZ) is a potassium-competitive acid blocker (P-CAB) used to treat conditions such as gastroesophageal reflux disease, peptic ulcer, and Helicobacter pylori infection. It exists in three solid forms: amorphous, Polymorph A, and Polymorph B. This study investigates the molecular basis of polymorph selection, focusing on conformational bias and solvent-mediated phase transformations (SMPTs). Methods: The conformational energy landscapes of two TPZ tautomers were constructed using relaxed torsion scans with the OPLS4 force field and validated by nuclear Overhauser effect (NOE)-based nuclear magnetic resonance (NMR). Hydrogen-bonded dimers were analyzed using DFT-D. Powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), solubility, and slurry tests were conducted using methanol, acetone, and water. Kinetic profiles were modeled with the Kolmogorov–Johnson–Mehl–Avrami (KJMA) equation. Results: Polymorph A was thermodynamically stable across all analyses. Both amorphous TPZ and Polymorph B converted to A in a solvent-dependent manner. Methanol induced direct A formation, while acetone showed a B → A transition. Crystallization was guided by solution conformers and hydrogen bonding. Conclusions: TPZ polymorph selection is governed by solution-phase conformational preferences, tautomerism, and solvent-mediated hydrogen bonding. DFT-D and NMR analyses showed that protic solvents favor the direct crystallization of stable Polymorph A, while aprotic solvents promote the transient formation of metastable Polymorph B. Elevated temperatures and humidity accelerate polymorphic transitions. This crystal structure prediction (CSP)-independent strategy offers a practical framework for rational polymorph control and the mitigation of disappearing polymorph risks in tautomeric drugs. Full article

The relationship between protein structure and function is intrinsically interconnected, as the structure of a protein directly determines its functional properties. To investigate the effects of temperature and pressure on protein function, this study employed ethyl carbamate (EC) hydrolase as a model food enzyme and conducted molecular dynamics (MD) simulations under varying temperature and pressure levels to elucidate its structure–function relationship. By systematically analyzing the dynamic changes in root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), hydrogen bonding, catalytic pocket conformation, and packing density under different temperature and pressure conditions, we revealed the structural adaptability of EC hydrolase. Furthermore, we analyzed the characteristics of EC hydrolase using molecular dynamics simulations with temperature and pressure levels, as well as conformational bias-based computer-aided engineering, providing both theoretical and experimental foundation for the adaptability mechanisms of enzymes under extreme conditions. Full article

Grey models have attracted considerable attention as a time series forecasting tool in recent years. Nevertheless, the linear characteristics of the differential equations on which traditional grey models rely frequently result in inadequate predictive accuracy and applicability when addressing intricate nonlinear systems. This study introduces a conformable fractional order unbiased kernel-regularized nonhomogeneous grey model (CFUKRNGM) based on statistical learning theory to address these limitations. The proposed model initially uses a conformable fractional-order accumulation operator to derive distribution information from historical data. A novel regularization problem is then formulated, thereby eliminating the bias term from the kernel-regularized nonhomogeneous grey model (KRNGM). The parameter estimation of the CFUKRNGM model requires solving a linear equation with a lower order than the KRNGM model, and is automatically calibrated through the Bayesian optimization algorithm. Experimental results show that the CFUKRNGM model achieves superior prediction accuracy and greater generalization performance compared to both the KRNGM and traditional grey models. Full article

This study investigates the integration of Artificial Intelligence (AI) in Religious Education (RE), a field traditionally rooted in spiritual formation and human interaction. Amid increasing digital transformation in education, theological institutions are exploring AI tools for teaching, assessment, and pastoral engagement. Using a critical literature review and analysis of institutional case studies, the paper examines the historical development of AI in education, current applications in general and theological contexts, and the ethical challenges it introduces, especially regarding decision making, data privacy, and bias as well as didactically grounded opportunities such as AI-mediated dialogic simulations. The study identifies both the pedagogical advantages of AI, such as personalization and administrative efficiency, and the risks of theological distortion, overreliance, and epistemic conformity. It presents a range of real-world implementations from institutions like Harvard Divinity School and the Oxford Centre for Digital Theology, highlighting best practices and cautionary approaches. The findings suggest that AI can enrich RE when deployed thoughtfully and ethically, but it must not replace the relational and formational aspects central to RE. The paper concludes by recommending policy development, ethical oversight, and interdisciplinary collaboration to guide responsible integration. This research contributes to the growing discourse on how AI can be aligned with the spiritual and intellectual goals of RE in a rapidly evolving digital age. Full article

Background: The three commercial Enterovirus 71 (EV71) inactivated vaccines which have effectively controlled the EV71 pandemic currently rely on inherent variable in vivo potency methods for batch release. To align with 3R (Replacement, Reduction, Refinement) principles and enhance quality control, this study referred to WHO guidelines and the European Pharmacopoeia to develop in vitro relative potency (IVRP) methods. Methods: Working standards tracing to phase 3 clinical vaccines were established. Manufacture-specific IVRP methods were developed and validated per ICH Q14/Q2(R2), utilizing conformational epitope-targeting neutralizing monoclonal antibodies (MAbs). One of the MAbs (CT11F9) recognition sites was clarified with Cryo-EM. Subsequently, the performance of IVRP was assessed using varied concentrations and heat-treated vaccines. The correlation between IVRP and in vivo methods was analyzed, followed by setting IVRP specifications. Results: The manufacturer-specific working standard exhibited ED50 values comparable to those of related phase 3 clinical vaccines. All IVRP methods achieved a relative bias/precision/total error ≤ 15%. The IVRP methods correlated with in vivo methods (p < 0.05, r > 0.9) can discriminate EV71 antigen concentrations (p < 0.01, r > 0.99) and indicate the stability of the vaccines. Cryo-EM was adopted to identify the epitopes recognized by CT11F9, revealing that this neutralizing antibody recognizes a conformational epitope spanning VP1-3 of the same protomer. Using 31–47 batches of commercial vaccines, IVRP specifications were proposed as 0.56–1.35, 0.58–1.40, and 0.54–1.50. Conclusions: Based on conformational epitope-targeting neutralizing MAbs, manufacturer-specific IVRP methods, which were sensitive to process variations and correlated with in vivo results, have been established. IVRP methods provide a reliable, animal-free alternative for EV71 vaccine batch release. Full article

Background: Alterations in the adrenergic system have been associated with the pathophysiology of Alzheimer’s disease (AD). A novel α_1A-adrenergic receptor (AR)-positive allosteric modulator (PAM), CCF219B, has been shown to outperform donepezil with rescue of AD cognition/memory deficits with a reduction in amyloid biomarkers and without cardiovascular side effects. Initial pharmacological analysis in transfected cell lines revealed a signal bias with increased efficacy (but not potency) of cAMP signaling and ligand selectivity for norepinephrine (NE). As most GPCR allosteric modulators change the potency of agonists, we hypothesized and now report that CCF219B induced additional aspects of its allosteric interactions with NE that may provide mechanistic insight. Methods: Using Rat-1 fibroblasts stably transfected with α_1A-AR, we determined the activation profile of pERK and p38 messengers by CCF219B in the presence of NE. Using membranes prepared from the stably transfected fibroblasts or from the brain of WT mice or the AD mouse model, hAPP(lon), equilibrium or kinetic radioligand-binding analyses were performed. Results: We identified p-ERK1/2 but not p38 as an additional signal pathway that is potentiated by CCF219B in the presence of NE. An analysis of binding studies of CCF219B in membranes derived from the brains of WT or hAPP(lon) mice revealed profiles that were time-dependent and resulted in an increase in α_1A-AR expression that was unaltered in the presence of cycloheximide or when performed at 37 °C. hAPP(lon) mice displayed a reduction in α_1A-AR-binding sites that were rescued upon prolonged incubation with CCF219B but also displayed a compensatory increase in α_1B/D-AR subtype expression. Binding kinetics reveal that CCF219B can decrease the association rate of ³H-NE but only in the presence of GTP. The association rate increased for the radiolabeled antagonist, ¹²⁵I-HEAT. There were no changes in the dissociation rate of either radiolabel. Conclusions: CCF219B affects the association but not the dissociation rate of NE and explains its ability to increase the active state of the receptor by promoting a pre-coupled conformation, consistent with increasing efficacy but not potency. Potentiation of pERK may contribute to CCF219B’s ability to confer neuroprotection and be pro-cognitive in AD. CCF219B’s ability to increase the expression of α_1A-AR provides a positive feedback loop and strengthens the hypothesis that α₁-AR subtypes may be involved in AD etiology and/or progression. Full article

Background: The four subtypes of G protein-coupled receptors (GPCRs) regulated by histamine play critical roles in various physiological and pathological processes, such as allergy, gastric acid secretion, cognitive and sleep disorders, and inflammation. Previous experimental structures of histamine receptors (HRs) with agonists and antagonists exhibited multiple conformations for the ligands and G protein binding. However, the structural basis for HR regulation and signaling remains elusive. Methods: We determined the cryo-electron microscopy (cryo-EM) structure of the H4R-histamine-Gi complex at 2.9 Å resolution, and predicted the models for all four HRs in the ligand-free apo and G protein subtype binding states using AlphaFold3 (AF3). Results: By comparing our H4R structure with the experimental HR structures and the computational AF3 models, we elucidated the distinct histamine binding modes and G protein interfaces, and proposed the essential roles of Y^6.51 and Q^7.42 in receptor activation and the intracellular loop 2 (ICL2) in G protein bias. Conclusions: Our findings deciphered the molecular mechanisms underlying the regulation of different HRs, from the extracellular ligand-binding pockets and transmembrane motifs to the intracellular G protein coupling interfaces. These insights are expected to facilitate selective drug discovery targeting HRs for diverse therapeutic purposes. Full article

Background/Objectives: International guidelines recommend the use of orthoses in subjects with cerebral palsy (CP), even though there is limited evidence of their effectiveness. Little is known about their effectiveness in children and adolescents with other types of neuromotor disability. Methods: The review protocol was recorded on the PROSPERO register (CRD42024509165) and conformed to the PRISMA guidelines. The inclusion criteria were any type of ankle–foot orthoses (AFOs); pediatric subjects with any non-acquired neuromotor disease; any type of outcome measure regarding gait performance; controlled studies; and those in the English language. Screening, selection, risk of bias assessment, and data extraction were performed by a group of independent researchers. Results: Fifty-seven reports were included, with most regarding CP; three involved subjects with Charcot–Marie–Tooth disease or Duchenne dystrophy. Nine were RCTs. A meta-analysis was performed for studies including subjects with CP. The meta-analysis demonstrated the effectiveness of AFOs in increasing stride length (MD −10.21 [−13.92, −6.51]), ankle dorsiflexion at IC (MD 9.66 [7.05, 12.27]), and peak ankle DF in stance (MD 5.72 [2.34, 9.09]) while reducing cadence (MD 0.13 [0.06, 0.17]) and the energy cost of walking (MD −0.02 [−0.03, −0.00]). The peak ankle power generated at push-off was significantly increased with flexible AFOs compared to rigid AFOs (MD 0.38 [0.30, 0.46]), but it decreased with both compared to walking barefoot or with shoes (MD −0.35 [−0.49, −0.22]). Evidence regarding DMD and CMT was limited but suggested opting for individualized flexible AFOs, which preserved peak ankle power generation. Conclusions: AFOs improve gait performance in CP. Flexible AFOs are preferable because they preserve the peak ankle power generated at push-off compared to rigid AFOs. Full article

Background: Hypophosphatemic rickets (HR) is a bone disorder affecting phosphate–calcium metabolism, with both skeletal and dental manifestations. This review aims to analyze dental manifestations of HR in children and, where possible, compare them to those in healthy children or affected adults. Methods: The protocol was registered at PROSPERO (CRD42024596022). The study conformed to the PRISMA guidelines. Three databases were searched for studies reporting the prevalence or incidence of any dental manifestation in children with HR. Risk of bias was assessed using JBI, RoB 2.0, and ROBINS-E tools, and Stata/SE 18.0 was used for meta-analysis. Meta-regression was used to examine the effects of therapy duration and mean age on dental manifestations’ prevalence. The study received no funding. Results: A total of 1308 records were identified, with 660 screened after removing duplicates. Forty-six studies were eligible for full-text evaluation; sixteen were included in the qualitative analysis and twelve in the meta-analysis. The dental manifestations observed included dental abscesses, developmental defects of enamel and dentin, dental caries, taurodontism, and large pulp chambers. Dental abscesses were the most common manifestation, with a pooled prevalence of 0.39. Meta-regression showed no association between therapy duration and abscess occurrence but revealed a negative association between mean age and abscess prevalence. Conclusions: Dental abscesses were the most frequent manifestation in children with HR. The role of therapy in improving oral health remains unclear due to insufficient data, indicating a need for further studies on the impact of HR on children’s oral health. Full article

Given the convenience with which information can now be acquired, it is crucial to analyze cases of potential misinformation and disinformation in postsecondary education. Instructor credibility judgments were measured using descriptive survey research, and the main objective was to investigate trends related to misinformation, credibility, trust, bias, and others in graduate students and on a graduate program basis. Participants were surveyed from a land grant institution in the southeast United States where 186 graduate students completed an electronic survey on the detection of misinformation and similar experiences. Graduate students were divided based on graduate program into STEM (sciences, technology, engineering, and mathematics) and non-STEM groups. Quantitative methodologies included validated questionnaires developed by researchers containing Likert-type scale questions. Chi-square tests of independence and frequencies served as primary analyses. Participants in both STEM and non-STEM groups detected the following: misinformation, bias, challenges, intimidation, risk of measurable consequences, pressure to conform, and skepticism from post-secondary instructors. There were significant differences between the type of student for trust in claims (p < 0.05), while the perception of potential consequences tended to be different between the types of graduate students (0.05 < p < 0.10). Participants in both STEM and non-STEM groups reported perception bias in science material presentation, with STEM students reporting less bias. Qualitative methodologies included optional open response boxes to provide supporting details or narratives. Reliable and validated thematic coding following served as the primary analysis. Students disciplined in STEM and non-STEM faced misinformation, bias, challenges, intimidation, risk of measurable consequences, pressure to conform, and skepticism from post-secondary instructors. Graduate students reported consistent instances of misinformation and bias about science and agriculture topics in both science and non-science-focused classrooms. Full article

This article presents validation and conformity testing of the Sentinel-3 Ocean Land Colour Instrument (OLCI) green instantaneous fraction of absorbed photosynthetically active radiation (FAPAR) and OLCI terrestrial chlorophyll index (OTCI) canopy chlorophyll content (CCC) products with fiducial reference measurements (FRM) collected in 2018 and 2021 over two sites (Las Tiesas—Barrax, Spain, and Wytham Woods, UK) in the context of the European Space Agency (ESA) Fiducial Reference Measurement for Vegetation (FRM4Veg) initiative. Following metrological principles, an end-to-end uncertainty evaluation framework developed in the project is used to account for the uncertainty of reference data based on a two-stage validation approach. The process involves quantifying uncertainties at the elementary sampling unit (ESU) level and incorporating these uncertainties in the upscaling procedures using orthogonal distance regression (ODR) between FRM and vegetation indices derived from Sentinel-2 data. Uncertainties in the Sentinel-2 data are also accounted for. FRM-based high spatial resolution reference maps and their uncertainties were aggregated to OLCI’s native spatial resolution using its apparent point spread function (PSF). The Sentinel-3 mission requirements, which give an uncertainty of 5% (goal) and 10% (threshold), were considered for conformity testing. GIFAPAR validation results revealed correlations > 0.95, RMSD ~0.1, and a slight negative bias (~−0.06) for both sites. This bias could be partly explained by the differences in the FAPAR definitions between the satellite product and the FRM-based reference. For the OTCI-based CCC, leave-one-out cross-validation demonstrated correlations > 0.8 and RMSDcv ~0.28 g·m⁻². Despite the encouraging validation results, conclusive conformity with the strict mission requirements was low, with most cases providing inconclusive results (driven by large uncertainties in the satellite products as well as by the uncertainties in the upscaling approach). It is recommended that mission requirements for bio-geophysical products are reviewed, at least at the threshold level. It is also suggested that the large uncertainties associated with the two-stage validation approach may be avoided by directly comparing with spatially representative FRM. Full article

This study examined the association between media and Instagram interaction patterns with weight bias among undergraduate nutrition students in the Brazilian Nutritionists’ Health Study. We also explored the potential mediating role of students’ own body image perception in these relationships. A total of 406 students (78% women) participated in this cross-sectional analysis. Sociodemographic data, media influence, Instagram interaction patterns, body image perception, and weight bias were assessed using semi-structured questionnaires. Findings indicated that exposure to fitness content on Instagram (β = 0.17, p < 0.001) and the pursuit of an ideal athletic body (β = 0.12, p = 0.034) were associated with increased weight bias. In contrast, engagement with body diversity content (β = −0.23, p < 0.001) and perceived pressure from media to conform to appearance ideals (β = −0.24, p < 0.001) had a mitigating effect on weight bias. Notably, body image perception did not mediate these relationships (p > 0.05). In conclusion, this study revealed a link between media exposure and weight bias among undergraduate nutrition students, independent of their body image perception. Developing social media literacy programs that encourage students to critically evaluate media content is imperative to reduce weight bias. Additionally, a deeper examination of the media content that contributes to weight bias and the potential need for targeted regulatory measures is warranted. Full article

Common challenges in cryogenic electron microscopy, such as orientation bias, conformational diversity, and 3D misclassification, complicate single particle analysis and lead to significant resource expenditure. We previously introduced an in silico method using the maximum Feret diameter distribution, the Feret signature, to characterize sample heterogeneity of disc-shaped samples. Here, we expanded the Feret signature methodology to identify preferred orientations of samples containing arbitrary shapes with only about 1000 particles required. This method enables real-time adjustments of data acquisition parameters for optimizing data collection strategies or aiding in decisions to discontinue ineffective imaging sessions. Beyond detecting preferred orientations, the Feret signature approach can serve as an early-warning system for inconsistencies in classification during initial image processing steps, a capability that allows for strategic adjustments in data processing. These features establish the Feret signature as a valuable auxiliary tool in the context of single particle analysis, significantly accelerating the structure determination process. Full article