Search Results (212)

This study develops and empirically evaluates a multilevel analytical framework linking AI-generated mathematical reasoning, students’ diagnostic reasoning, and mathematics achievement in AI-supported mathematical problem solving. A classroom intervention with 76 undergraduate Calculus A students generated 380 repeated student–problem observations across five mathematical tasks and three instructional formulations. Students evaluated AI-generated solutions for final-answer correctness, methodological correctness, and procedural completeness, identified mathematical errors, and proposed corrections before completing an individual posttest. Hierarchical mixed-effects models and student-level achievement analyses were used to examine successive stages of the learning process. Instructional formulation was not significantly associated with the quality of AI-generated mathematical reasoning. Final-answer correctness, methodological correctness, and procedural completeness showed substantial task-specific variation. Instructional formulation was significantly associated with students’ error detection, with higher detection performance under Instruction Types B and C than under Type A, while AI-generated response quality remained comparable across instructional formulations. Baseline mathematical proficiency was the strongest predictor of posttest performance. Students’ Mean Error-Detection Event Rate was positively associated with posttest achievement. No robust overall independent association between instructional formulation and posttest achievement was identified after baseline adjustment. Students’ diagnostic engagement with AI-generated mathematical reasoning was associated with subsequent mathematics achievement, supporting the analysis of diagnostic reasoning as a distinct component of AI-supported mathematics learning. Full article

Nanobiochar has attracted increasing attention as a redox-active carbon nanomaterial with potential applications beyond its traditional roles in environmental remediation and adsorption technologies. When integrated into hydrogel matrices, nanobiochar may provide a unique combination of physicochemical and biological functionalities, including reactive oxygen species (ROS) modulation, antimicrobial activity, high adsorption capacity, and localized therapeutic delivery. Such properties are particularly relevant to emerging wound-healing and regenerative medicine applications; however, the biological mechanisms governing the performance of nanobiochar–hydrogel systems remain poorly understood. Because direct studies on nanobiochar–hydrogel therapeutic systems remain scarce, this review integrates evidence from the limited nanobiochar literature together with evidence from studies on conventional biochar, hydrogel biomaterials, and related carbon nanomaterial to critically evaluate emerging biological mechanisms and identify future research priorities. This review combines bibliometric analysis with mechanistic evaluation to assess the potential of nanobiochar–hydrogel systems as therapeutic biomaterials while highlighting critical knowledge gaps limiting their development. Bibliometric findings reveal that research on biochar–hydrogel composites is dominated by environmental remediation, adsorption processes, and material characterization, whereas investigations addressing biological responses and therapeutic functionality remain limited. Building upon these observations, this review examines nanobiochar surface chemistry, electron transfer behavior, and redox-active properties that may influence ROS regulation at biological interfaces. Particular emphasis is placed on biointerface interactions, including protein adsorption, protein corona formation, cellular uptake pathways, and the influence of hydrogel-mediated exposure on biological responses. The review further evaluates potential antimicrobial mechanisms, redox-sensitive signaling pathways, cytocompatibility assessment strategies, and the behavior of nanobiochar-containing systems under physiologically relevant conditions. Current evidence indicates a strong reliance on chemical antioxidant assays and short-term viability measurements, while mechanistic investigations involving intracellular ROS regulation, inflammatory signaling, mitochondrial function, and gene expression responses remain scarce. Collectively, the literature discussed in this article highlights the substantial gap between material development and biological validation and provides a framework for future studies aimed at evaluating the suitability of nanobiochar–hydrogel systems for wound-healing and regenerative applications. Full article

The increasing presence of SARS-CoV-2 antivirals (SASs) in wastewater threatens aquatic ecosystems, making it necessary to better understand their removal efficiency during biological treatment. This study evaluates the removal percentages, kinetic mechanisms, and toxicity profiles of six SASs, daclatasvir (DCV), darunavir (DRV), favipiravir (FAV), lopinavir (LOP), remdesivir (REM), and ritonavir (RIT), using activated sludge. A full factorial design combined with response surface methodology (RSM) was used to assess the impact of pH, temperature (T), and mixed liquor suspended solids (MLSS) on SAS removal and microbial stability. The results distinguished two dominant removal pathways. DCV and LOP were primarily removed by adsorption, whereas DRV, FAV, REM and RIT were predominantly removed through biodegradation involving enzymatic transformation and bacterial co-metabolism. RSM achieved a desirability score of 0.772 and identified the optimal operating conditions (pH = 6.08, MLSS = 4.41 g/L, and T = 44.99 °C), resulting in removal efficiencies above 93% for all compounds except DRV, which remained the limiting compound with a maximum removal efficiency of 66%. Perturbation analysis showed that all tested factors have a distinct influence on process performance. These established kinetic trends should support further investigations into advanced biological wastewater treatment methods and precise ecotoxicity profiling of emerging biotransformation products. Full article

We consider nearapproaching, a simple generalisation of pseudonearness and approach distances. The central idea in an approach space $(X,d)$ in the sense of Lowen is that of a distance d, which is a function on $X\times 2^X$ to $[0,\infty ]$. Of fundamental importance is the fact that such a distance can be defined not only in metric spaces, but also in topological spaces, uniform spaces, and related structures. Pseudonearness structures on a set X consist of pairs $({\mathcal{B}}^X,N)$, where ${\mathcal{B}}^X$ is a bornology and N is a nearoperator from ${\mathcal{B}}^X$ to $\underline{P}\left(\underline{P}\left(\underline{P}X\right)\right)$, satisfying certain near axioms. In this framework, bornologies, generalised Kuratowski operators, pseudoproximity structures, and, last but not least, classical nearness spaces can all be unified within a single setting. In our treatment of approaching, we define the corresponding spaces by focusing on functions $\tau$ from $CX\subset \underline{P}(\underline{P}\left(X\right)$ into the set of functions from ${\mathcal{B}}^X$ into the closed interval $[0,\infty ]$, known as targets, which we compare setwise, where ${\mathcal{B}}^X$ is a boundedness structure. Thus, a target can be regarded as a map that measures how close a collection $\mathcal{S}\in CX$ is to a bounded set $B\in {\mathcal{B}}^X$. Full article

Drug repurposing presents as a promising strategy in oncology, particularly for urological prostate and bladder cancers, where resistance to current therapy remains a challenge. This study evaluated the anticancer potential of three antiretroviral drugs, namely ritonavir (RIT), saquinavir (SAQ), and rilpivirine (RPV), in PC-3 and UM-UC-5 cancer cell lines, using MTT, clonogenic, wound healing, toxicity assessment with fibroblast cells, and DCFDA assays; this last method included efavirenz (EFV) and etravirine (ETV) for intracellular reactive oxygen species (ROS) production. RIT and SAQ showed stronger antiproliferative effects than RPV, with lower concentration- and cell-line-dependent activity, while clonogenic assays confirmed a reduction in long-term proliferation, particularly for RIT in both cell lines and SAQ for UM-UC-5. In contrast, effects on cell migration were limited for all drugs. ROS production was cell-dependent, with EFV increasing ROS in PC-3 and SAQ and RIT in UM-UC-5 cells. Generally, all drugs showed minimal toxicity in non-malignant cells, with SAQ exhibiting some toxicity but only for concentrations higher than those required for anticancer activity. Overall, these findings suggest that antiretroviral, especially protease inhibitors, may cause anticancer effects, although these are concentration- and context-dependent, and further investigation is needed to understand the mechanisms involved. Full article

Effective monitoring of insect populations is essential for sustainable pest management and for supporting Integrated Pest Management (IPM) strategies that reduce reliance on chemical pesticides. Bioacoustic methods have recently emerged as a promising approach for monitoring insects by analyzing the sounds and vibrations they produce during activities such as feeding, movement, and communication. This review examines the application of bioacoustics in insect monitoring and pest management, with particular emphasis on recent advances in artificial intelligence (AI) and automated detection technologies. The biological foundations of insect sound production, acoustic monitoring technologies, and AI-based analytical methods are discussed. Machine learning and deep learning models enable automated detection and classification of insect species based on acoustic signals, facilitating early pest detection and biodiversity monitoring. Bioacoustics has been applied to detect and identify insect pests, monitor stored-product insects, and manipulate insect behavior using acoustic and vibrational signals. Despite these advances, challenges remain, including environmental noise interference, limited acoustic datasets, and technical constraints of monitoring systems. Future research should focus on improving datasets, signal processing methods, and the integration of bioacoustics monitoring with precision agriculture and IPM frameworks to support sustainable crop protection. Full article

Noonan syndrome (NS) is a paradigmatic rare, genetically heterogeneous, multisystem disorder belonging to the RASopathies family, caused by dysregulated RAS/MAPK signaling. It is characterized by distinctive craniofacial features, postnatal short stature, and a high prevalence of congenital cardiac defects, with pulmonary valve stenosis (PS) and hypertrophic cardiomyopathy (HCM) being the hallmark lesions. First described by Dr. Jacqueline Noonan in 1968, the molecular era began with the discovery of PTPN11 mutations in 2001, revolutionizing diagnosis, risk stratification, and understanding of pathogenesis. Strong genotype–phenotype correlations now guide prognosis and personalized management; for instance, RAF1 and RIT1 variants confer a high risk of severe, early-onset HCM, while PTPN11 is strongly linked to dysplastic PS. Cardiac involvement remains the central determinant of long-term outcomes, requiring continuous surveillance from the prenatal period through adulthood. Management is inherently multidisciplinary, addressing endocrine, hematologic, neurodevelopmental, and oncologic aspects. Recent consensus statements emphasize the critical need for structured transition from pediatric to adult care. Novelty arises from the potential of MEK inhibitors as targeted therapies for severe HCM and lymphatic complications. This review provides a comprehensive update on NS, integrating foundational clinical knowledge with contemporary molecular insights, advanced cardiologic management, and emerging frontiers in therapy and diagnostics, underscoring the necessity of a proactive, lifelong, and personalized care approach. Full article

This study assesses liquidity, profitability, and working capital management (WCM) strategy in Polish manufacturing companies in the pressure-casting industry, drawing on evidence from the pre-COVID-19, COVID-19, and Russia–Ukraine war periods. Using panel data from 19 companies representing 90% of the Polish aluminum diecasting industry, we employ non-parametric tests (Mann–Whitney U and Kruskal–Wallis) to analyze the data. The period after the COVID-19 crisis coincides with the Russian–Ukrainian war. These countries are Poland’s neighbors. This period of uncertainty for Poland has led to supply chain disruptions and reduced investments. For manufacturing companies, this is dangerous because they have limited development opportunities. The results indicate the adoption of a conservative WCM strategy in Polish aluminum foundries during the pre-COVID-19, COVID-19, and Russia–Ukraine war periods, characterized by increased inventory levels, extended operating cycles in large firms. Additionally, the results showed reduced the level of receivables in large companies and visible decrease in the level of financial liquidity and profitability—however, these differences are not statistically significant. Polish aluminum foundries are adapting their WCM strategies toward an optimal, conservative approach that incorporates both safe and risky elements to ensure continued operations and profits. In addition, larger Polish aluminum foundries exhibit distinct liquidity patterns relative to smaller foundries, particularly in indicators of inventory, receivables, and fixed assets. In addition, the Russia–Ukraine war period exhibits distinct liquidity characteristics in Polish aluminum foundries compared with the COVID-19 and pre-COVID-19 periods, particularly in inventory turnover and operating cycle. The results of this study offer several novel contributions to the existing literature on financial security indicators by examining unexplored factors related to size and period. The results of this study have several practical implications for business leaders seeking to adopt an optimal liquidity, profitability, and WCM strategy. Full article

Radiation-induced trismus (RIT) is a common and function-limiting late complication of radiotherapy for head and neck cancers, particularly when the masticatory muscles and temporomandibular joint receive high doses. Despite advances in intensity-modulated radiotherapy, RIT remains a significant survivorship problem, and robust biological biomarkers capable of predicting individual susceptibility are lacking. Heat shock protein 27 (HSP27; HSPB1) is a small heat shock protein that regulates multiple cellular stress responses, including proteostasis, cytoskeletal dynamics, redox homeostasis, apoptosis, and inflammatory signaling. In head and neck malignancies, HSP27 overexpression has been associated with treatment resistance and fibrosis-prone tissue remodeling. Experimental studies further demonstrate that HSP27 promotes transforming growth factor-β-mediated myofibroblast differentiation and extracellular matrix deposition, whereas pharmacologic or genetic inhibition attenuates radiation- or bleomycin-induced pulmonary fibrosis in vivo. Evidence from skeletal muscle biology also indicates that HSP27 modulates muscle integrity, denervation-associated atrophy, inflammatory signaling, and cytoskeletal stability. Although HSP27 has been widely investigated in radiation responses, fibrosis, and skeletal muscle stress adaptation, its potential involvement in the pathogenesis of RIT has not been systematically examined. This review proposes a conceptual framework in which HSP27 functions as an integrative molecular mediator linking radiation-induced oxidative stress, endothelial injury, and fibro-atrophic remodeling within the masticatory apparatus. By integrating current evidence on the epidemiology, dosimetric determinants, imaging correlates, and pathophysiology of RIT with the structural and functional biology of HSP27, this review provides the first tissue-specific synthesis of molecular stress signaling and clinical mechanisms relevant to RIT susceptibility. We further suggest that HSP27 signaling may influence susceptibility to fibro-neuromuscular injury in irradiated masticatory tissues. Given the absence of direct experimental or clinical evidence in this setting, these considerations are derived from mechanistic convergence across related biological systems and should be interpreted as biologically plausible but unproven, with potential implications for future biomarker development and biologically informed prevention strategies. Full article

Imitation is crucial for social learning, yet children with autism spectrum disorder (ASD) often show atypical imitation abilities. To probe the neural dynamics that precede overt imitation, electroencephalography (EEG)—with a focus on α (8–12 Hz) and β (13–30 Hz) activity commonly linked to action observation and sensorimotor processing—was used to index pre-imitation processing in preschool-aged children with ASD. Grounded in the social motivation framework, this study combined an EEG experiment and a naturalistic behavioral intervention. In Study 1, 11 preschool children with ASD completed an action-observation (pre-imitation) task under low- versus high-sociality video conditions. Time–frequency and spectral analyses were conducted to compare α- and β-band responses across conditions. In Study 2, four children received a six-week Reciprocal Imitation Training (RIT) program, and imitation and social-communication outcomes were assessed pre-, mid-, and post-intervention. The results showed that low-sociality stimuli elicited stronger frontal and prefrontal power increases in both α and β bands, whereas high-sociality stimuli elicited more temporally dynamic β-band responses but with lower overall power engagement. Although inferential support was limited by sample size, behavioral trends suggested improvements following RIT in imitation and related social functioning, with larger gains in children with mild-to-moderate ASD. Together, these findings suggest that social context modulates pre-imitation neural activity in ASD and that socially grounded imitation training may support broader social development. Full article

Background/Objectives: Malignant mesothelioma has a poor prognosis and limited therapeutic options. C-ERC/mesothelin is highly expressed in mesotheliomas and is a potential target for radioimmunotherapy (RIT). This study evaluated the radiolabeled anti-C-ERC/mesothelin antibody mAb 22A31 as a therapeutic agent. Methods: C-ERC/mesothelin expression in mesothelioma cell lines was assessed by Western blotting, and the specific binding of ¹²⁵I-labeled mAb 22A31 was examined. Biodistribution of ¹¹¹In-labeled mAb 22A31 was evaluated in a mesothelioma cell line, MSTO-211H tumor-bearing mice. The therapeutic efficacy of ⁹⁰Y-labeled mAb 22A31 was evaluated in subcutaneous and pleural dissemination models. Results: mAb 22A31 showed specific binding considering the level of C-ERC/mesothelin expression in each mesothelioma cell line. ¹¹¹In-mAb 22A31 accumulated in tumors with minimal uptake in normal tissues. ⁹⁰Y-mAb 22A31 significantly delayed the growth of subcutaneous tumors and improved survival in a pleural dissemination model. Conclusions: Radiolabeled mAb 22A31 specifically targeted C-ERC/mesothelin and demonstrated therapeutic efficacy in a mesothelioma xerograph model. Therefore, ⁹⁰Y-mAb 22A31 is a promising RIT agent and supports the further development of C-ERC/mesothelin-targeted therapy for mesothelioma. Full article

Intervertebral disc degeneration is characterized by inflammation, extracellular matrix breakdown, and neurovascular ingrowth, processes that contribute to discogenic, chronic back pain. The transient receptor potential canonical 6 (TRPC6) channel is a calcium-permeable ion channel implicated in inflammation and pain signaling in multiple tissues; however, its functional role in human disc cells remain unknown. Here, we investigated the expression, activation, and downstream consequences of TRPC6 activation using Hyp9, a pharmacological activator of TRPC6. TRPC6 transcripts were consistently detected across all donors examined (n = 17). Functional TRPC6 activation induced a rapid, dose-dependent calcium (Ca²⁺) influx across 0.5–100 µM Hyp9. TRPC6 activation did not reduce metabolic activity or increase cytotoxicity at concentrations commonly used for in vitro TRPC6 activation. Mechanistically, TRPC6 activation induced mitogen-activated protein kinase (MAPK) and nuclear factor kappa B (NF-κB) pathways, as demonstrated by increased phosphorylation of p38 and extracellular signal-regulated kinase (ERK), degradation of the inhibitor of κB-alpha (IκB-α), and increased nuclear translocation of the NF-κB p65 subunit. Downstream of these early signaling events, TRPC6 activation elicited a robust inflammatory and catabolic response with upregulation of IL-6, IL-8, COX-2, MMP-1, MMP-3, NGF, and VEGF, with corresponding increases in protein secretion. These findings identify TRPC6 as an important signaling node linking calcium influx to inflammatory, catabolic, and neuro- and angiogenesis-associated pathways in disc cells, highlighting TRPC6 as a potential therapeutic target in degenerative disc disease. Full article

To produce strong and wear-resistant tools for the rock drilling industry, the most commonly used metal matrix composites contain the reinforcing phase of cemented carbide. There are numerous research reports on attempts to improve the performance of WC-Co composites. The paper is a continuation of previously reported research on the SPS-processed WC–6 wt.%Co metal matrix composites with yttria-stabilized zirconia (YSZ) addition in amounts of 4 wt.% and 10 wt.%. The sintered specimens were polished and underwent the microindentation tests with a Vickers shape diamond tip. The following parameters were measured: stiffness S, the Poisson number ν, indentation creep C_IT, relaxation R_IT, indentation hardness H_IT, indentation Vickers hardness HV_IT, Martens hardness HM, reduced modulus E*, and indentation elastic modulus E_IT. The tests revealed hardness values of 16.2–17.0 GPa and indentation elastic moduli in the range of 607–670 GPa. Moreover, respective plastic and elastic parts of the indentation work W_plast and W_elast were determined. It was found that YSZ addition slightly reduced hardness and modulus, but all the three wear parameters, H/E, H³/E², and 1/(E²H), increased after addition of zirconia. Specifically, for 10 wt.% ZrO₂ H/E increased by 5%, H³/E² by 7%, while 1/(E²H) by 27% compared to 94WC–6Co composition. Full article

Targetless LiDAR–camera extrinsic calibration remains challenging due to unreliable cross-modal correspondences and sensitivity to initialization. We present a targetless extrinsic calibration framework based on class-agnostic boundary mask alignment in a shared image-plane representation. This scheme first constructs consistent LiDAR–camera mask pairs from image-plane depth and intensity projections of LiDAR data and camera images. It then obtains robust initial pose candidates through bounded rotation-only global initialization and refines them using a computationally efficient stochastic gradient approximation to estimate the optimal extrinsic parameters. Experiments on the KITTI benchmark demonstrate a superior accuracy–runtime trade-off compared with a segmentation-based global optimization baseline, while real-world driving tests confirm stable cross-modal alignment under vibration and inter-modal timing jitter. Full article

Receiver-initiated MAC protocols, such as the IEEE 802.15.4e RIT scheme, are promising for energy-efficient communication in multi-hop wireless sensor networks. However, their practical use requires a better understanding of how multiple contention-avoidance mechanisms interact under realistic network conditions. This study develops an ns-3 implementation of an RIT-compliant receiver-initiated MAC protocol together with a flexible evaluation framework that enables selective activation of representative enhancement strategies, including carrier-sensing options for data and beacon transmissions and randomization of beacon intervals. Four realistic network scenarios were designed to simulate practical deployment settings. Simulation results revealed that the effectiveness of these enhancement strategies varied significantly depending on network load and topology. In particular, beacon interval randomization, although often assumed to improve robustness, was found to degrade performance under low-load conditions, indicating that even widely adopted mechanisms may behave differently depending on operational environments. Conversely, CSMA-based approaches provided consistent improvements in transmission reliability. These observations highlight the importance of considering environmental factors and parameter configurations when enabling enhancement mechanisms. Overall, the proposed platform provides a reproducible and unified environment for fair comparison of receiver-initiated MAC protocols and their optional mechanisms, offering practical insights for selecting appropriate configurations in real sensor network deployments. Full article