Search Results (29,227)

Production of ferrochrome alloy is carried out using carbon as a reductant in a Submerged Arc Furnace (SAF). Carbothermic reduction of chromite ore results in high CO₂ emissions, and alternative reductants such as H₂, wherein H₂O is the only by-product, have become attractive potential alternatives. Before utilizing H₂ as a reductant, it is crucial to carry out a comprehensive study on the reaction kinetics with the view to aid the design and operation of reactors that facilitate the reduction process. The current study determined the kinetic parameters for isothermal and non-isothermal pre-reduction of chromite with H₂ in a thermogravimetric furnace. Results from powder X-ray diffraction and scanning electron microscopy determined the mineralogical variations between the feed and the pre-reduced samples, as well as the variation between isothermally and non-isothermally treated samples. The mass loss data indicates that longer reduction times are required to reach complete reduction. The apparent activation energy for the isothermal and non-isothermal pre-reduction tests was found to be 105 and 124 kJ/mol, respectively. The mineralogical observations for pre-reduced samples at 1300 °C and 1500 °C showed that samples treated at lower temperatures (1300 °C) displayed consistent textures and Fe-Cr droplets along rims of partially altered chromite (PAC), which suggested higher metallization at this temperature. Higher temperatures (1500 °C), on the other hand, resulted in poor metallization, possibly because higher temperatures are often associated with a collapsed pore network, which results in poor diffusion rates, thus hindering complete reduction. Full article

Oat, an important cereal and forage crop, is significantly affected by drought stress during production. However, the molecular mechanisms underlying oat’s response to drought stress remain largely unknown. In this study, K-means clustering classified 28 oat varieties into drought-tolerant (Muda, Mengshi No. 1) and drought-sensitive (Heike, Haywire) groups, with grey relational analysis further verifying MS as the most drought-tolerant and HK as the most drought-sensitive variety. Under drought stress, drought-tolerant and drought-sensitive varieties showed notable differences in leaf chlorophyll content, osmoregulation substances, and the activities of antioxidant enzymes. Transcriptomic analysis showed that 1915 differentially expressed genes (DEGs) were shared among all comparisons between treatment groups and the control group. KEGG pathway analysis revealed enrichment in pathways such as plant–pathogen interactions, plant hormone signal transduction, and starch and sucrose metabolism. In the signal transduction of plant hormones, eight PP2C genes associated with ABA signaling were increased, indicating that oats might respond to drought by enhancing metabolic activities via the ABA signaling pathway. WGCNA identified gene modules significantly associated with physiological traits. Notably, Mantel tests revealed that six core genes exhibited a positive correlation with CAT activity in the drought-tolerant variety, while showing an opposite trend in the sensitive variety. This study provides insights into the mechanisms of drought tolerance in oats and aids in the molecular breeding of drought-tolerant varieties. Full article

Liver fibrosis is a significant consequence of severe liver injury resulting from viral hepatitis, alcohol, and metabolic dysfunction. Progressive fibrosis and ultimate cirrhosis are leading causes of morbidity and mortality worldwide, generally irreversible and poorly targeted by current therapies. Traditional in vitro models and animal models mostly fail to fully recapitulate human multicellular crosstalk, extracellular matrix (ECM) remodeling, and the chronic, immune modulated nature of the disease. Recent advances in three-dimensional (3D) cell culture models including organoids, spheroids, bioprinted constructs, and organ-on-a-chip systems are advantageous for reconstructing cellular diversity and mechanical microenvironments to understand pathophysiology and aid in drug discovery. Emerging multi-organ models are capable of incorporating microbiome derived cues and using multi-omics readouts and imaging-enabled mechanistic dissection for more predictive anti-fibrotic screening. These technologies align well with the recent Modernization 3.0 regulation and New Approach Methodologies by the Food and Drug Administration (FDA) and recent EU Pharmaceutical Reform. This review summarizes the pathophysiology of liver fibrosis, the current landscape of 3D human liver models, and examines how microbiome interfaces modulate fibrogenesis. Full article

Background: Current histopathology- and molecular-based gold standards for diagnosing adult diffuse gliomas (ADGs) have inherent limitations in reproducibility and interobserver concordance, while being time-intensive and resource-demanding. Although hyperspectral imaging (HSI)-based computer-aided pathology shows potential for automated diagnosis, it often yields suboptimal accuracy due to the lack of complementary spatial and structural tumor information. This study introduces a multimodal fusion framework integrating HSI with routinely acquired preoperative magnetic resonance imaging (MRI) to enable automated, high-precision ADG diagnosis. Methods: We developed the Hyperspectral Attention Fusion Network (HAFNet), incorporating residual learning and channel attention to jointly capture HSI patterns and MRI-derived radiomic features. The dataset comprised 1931 HSI cubes (400–1000 nm, 300 spectral bands) from histopathological patches of six major World Health Organization (WHO)-defined glioma subtypes in 30 patients, together with their routinely acquired preoperative MRI sequences. Informative wavelengths were selected using mutual information. Radiomic features were extracted with the PyRadiomics package. Model performance was assessed via stratified 5-fold cross-validation, with accuracy and area under the curve (AUC) as primary endpoints. Results: The multimodal HAFNet achieved a macro-averaged AUC of 0.9886 and a classification accuracy of 98.66%, markedly outperforming the HSI-only baseline (AUC 0.9267, accuracy 87.25%; p < 0.001), highlighting the complementary value of MRI-derived radiomic features in enhancing discrimination beyond spectral information. Conclusions: Integrating HSI biochemical and microstructural insights with MRI radiomics of morphology and context, HAFNet provides a robust, reproducible, and efficient framework for accurately predicting 2021 WHO types and grades of ADGs, demonstrating the significant added value of multimodal integration for precise glioma diagnosis. Full article

Advances in artificial intelligence (AI), soft robotics, and miniaturized imaging technologies have accelerated the development of endorobotic platforms that aim to enhance detection accuracy and improve patient experience. In this narrative review, we synthesize evidence on AI-assisted detection and characterization systems (CADe/CADx), robotic locomotion mechanisms, adhesion strategies, imaging modalities, and material and power constraints relating to next-generation CRC screening technologies. Reported performance metrics are interpreted within their original methodological contexts, acknowledging the heterogeneity of datasets, limited representation of diverse populations, underreporting of negative findings, and scarcity of large, real-world comparative trials. We introduce a conceptual translational framework that links engineering design principles with validation needs across in silico, in vitro, preclinical, and clinical stages, and we outline safety considerations, workflow integration challenges, and sterility requirements that influence real-world deployability. Regulatory alignment is discussed using the U.S. FDA Total Product Life Cycle (TPLC) and Good Machine Learning Practice (GMLP) frameworks to highlight expectations for data quality, model robustness, device–software interoperability, and post-market monitoring. Collectively, the evidence demonstrates promising technological innovation but also highlights substantial gaps that must be addressed before AI-enabled endorobotic systems can be safely and effectively integrated into routine CRC screening. Continued interdisciplinary work, supported by rigorous validation and transparent reporting, will be essential to advance these technologies toward meaningful clinical impact. Full article

Objectives: The differential diagnosis of ameloblastoma and odontogenic keratocyst is essential for surgical planning and patient counseling. While deep learning (DL)-based methods show promising potential in this domain, their clinical translation remains challenging due to insufficient interpretability. This study aims to introduce segmentation-guided preprocessing approaches to provide support for the clinical implementation of computer-aided diagnosis systems. Methods: This study evaluated the performance of an InceptionV3 model on 128 pathologically confirmed CBCT scans (AME: 64; OKC: 64) by 5-fold cross-validation. Four experimental inputs were compared: (1) Original slice; (2) Bounding-box ROI; (3) Precise segmentation ROI; and (4) Moderately expanded ROI. All models were trained under the same settings. Assessment was conducted on both the slice and patient levels, incorporating accuracy, recall, precision, F1-score, and the area under the receiver operating characteristic curve (AUC). Grad-CAM visualization and confidence curve analysis were employed to verify models’ attention patterns and diagnostic confidence. Results: All models based on segmentation-guided ROI significantly outperformed models based on original slice. The moderately expanded ROI achieved optimal performance. The bounding-box ROI provided competitive performance with higher recall. Grad-CAM confirmed improved attention localization, while confidence curve analysis showed more consistent and reliable prediction patterns across slices. Conclusions: Segmentation-guided preprocessing represents an effective and clinically relevant approach for jaw lesion diagnosis and enhances interpretability. Full article

Background/Objectives: Older adults with hearing loss frequently report increased listening effort and fatigue, particularly in complex auditory environments. These subjective experiences may reflect increased cognitive resource allocation during both auditory and visual tasks, yet the impact of hearing aids on task-related effort and fatigue remains unclear. This study examined subjective effort and fatigue in experienced older adult hearing aid users while completing cognitively demanding auditory and visual tasks in quiet and background noise, with and without hearing aids. Methods: Thirty-one adults aged 60–87 years completed a cognitive battery assessing inhibition, attention, executive function, and auditory and visual working memory across four listening conditions: aided-quiet, unaided-quiet, aided-noise, and unaided-noise. Subjective effort was measured using the NASA Task Load Index, and task-related fatigue was assessed using a situational fatigue scale. Linear mixed-effects models controlled for age and pure-tone average hearing thresholds. Results: Participants reported significantly lower effort and fatigue in quiet compared to background noise, regardless of hearing aid use. The aided-quiet condition was rated as the least effortful and fatiguing, whereas the unaided-noise condition was rated as the most demanding. Subjective effort and fatigue were moderately to strongly correlated across conditions, particularly in noise. Auditory working memory performance was significantly associated with subjective fatigue across listening conditions, while visual working memory was not associated with effort or fatigue. Hearing aid use did not produce significant reductions in effort or fatigue across conditions. Conclusions: Background noise substantially increases perceived task-related effort and fatigue during cognitively demanding auditory and visual tasks in older adults with hearing loss. While hearing aids did not significantly reduce effort or fatigue across conditions, optimal listening environments were associated with the lowest subjective reports. Auditory working memory emerged as a key factor related to fatigue, highlighting the interplay between hearing, cognition, and subjective listening experiences in older adulthood. Full article

Hexoses, particularly glucose, are one of the most essential molecules for sustaining life; therefore, reliable methods for their analysis are very important. In our study, we present a qualitative and quantitative approach for analysing hexoses using MALDI IMS (Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging) with betaine aldehyde derivatisation and a CHCA (α-Cyano-4-hydroxycinnamic acid) matrix in positive ionisation mode. In this study, we demonstrated betaine aldehyde derivatisation of glucose from dried droplets and explored the analysis of hexoses in brain and liver tissue slices. We assessed whether our method could distinguish between mannose, galactose, glucose, and fructose and optimised the preparation of a biomimetic calibration curve using stable-isotope labelled glucose for hexose analysis. For this purpose, we investigated the number of betaine aldehyde layers required to obtain a proper calibration curve; examined whether changes in the spray nozzle position during CHCA matrix deposition could facilitate analysis and investigated how storage conditions influenced the calibration curve analysis. Finally, we optimised the technique for liver and brain analysis and assessed variations in hexose levels between brain, liver, kidney, and spinal cord tissues from control and morphine-addicted animals. We hope that our biomimetic approach to creating the calibration curve will be helpful for quantitative analysis and aid in developing various quantitative methods for assessing endogenous substances. Full article

The importance of statistical distributions in representing real-world scenarios and aiding in decision-making is widely acknowledged. However, traditional models often face limitations in achieving optimal fits for certain datasets. Motivated by this challenge, this paper introduces a new probability distribution termed the weighted sine generalized Kumaraswamy (WSG-Kumaraswamy) distribution. This model is constructed by integrating the Kumaraswamy baseline distribution with the weighted sine-G family, which incorporates a trigonometric transformation to enhance flexibility without adding extra parameters. Various statistical properties of the WSG-Kumaraswamy distribution, including the quantile function, moments, moment-generating function, and probability-weighted moments, are derived. Maximum likelihood estimation is employed to obtain parameter estimates, and a comprehensive simulation study is performed to assess the finite-sample performance of the estimators, confirming their consistency and reliability. To illustrate the practical advantages of the proposed model, two real-world datasets from epidemiology and reliability engineering are analyzed. Comparative evaluations using goodness-of-fit criteria demonstrate that the WSG-Kumaraswamy distribution provides superior fits compared to established competitors. The results highlight the enhanced adaptability of the model for unit-interval data, positioning it as a valuable tool for statistical modeling in diverse applied fields. Full article

Background/Objectives: Early identification of vasculitic acute kidney injury (AKI) is crucial for timely immunosuppression and improved renal outcomes; however, noninvasive adjunctive diagnostic tools remain limited. Renal elastography, a noninvasive technique that quantifies renal cortical stiffness, has been primarily investigated in chronic kidney disease, whereas evidence in acute kidney injury is scarce. This study aimed to evaluate the diagnostic utility of renal shear wave elastography for differentiating vasculitic from non-vasculitic AKI and to explore the association between baseline renal cortical stiffness and vasculitic renal outcomes. Materials and Methods: This prospective observational study included three groups: vasculitic AKI, non-vasculitic AKI, and healthy controls. Renal cortical stiffness was measured at admission using two-dimensional shear-wave elastography (2D-SWE) by radiologists blinded to clinical information. After clinicopathological confirmation of definitive diagnoses, between-group comparisons were performed and the diagnostic performance of elastography was evaluated. Additionally, in a biopsy-confirmed immunoglobulin A vasculitis nephritis (IgAVN) cohort (n = 12), baseline elastography measurements were examined in relation to one-year renal outcomes to explore potential prognostic associations. Results: The vasculitic AKI group exhibited significantly higher mean renal cortical stiffness values (9.5 ± 1.9 kPa) compared with both healthy controls (5.53 ± 0.92 kPa) and the non-vasculitic AKI group (6.61 ± 1.89 kPa) (both p < 0.01). Mean renal cortical stiffness demonstrated good diagnostic performance for distinguishing vasculitic from non-vasculitic AKI (AUC 0.86, 95% CI 0.73–0.97), with an optimal threshold of 6.79 kPa yielding 91% sensitivity and 72% specificity. In the prospective one-year follow-up of the IgAVN subcohort (n = 12), patients with unfavorable renal outcomes tended to have higher baseline renal cortical stiffness compared with those with favorable outcomes [median (min–max), 11.2 (10.8–13.3) vs. 9.1 (5.6–11.2), p = 0.046]. Conclusions: These findings suggest that renal elastography may aid in distinguishing vasculitic from non-vasculitic acute kidney injury and may provide exploratory information on the relationship between baseline cortical stiffness and renal outcomes in IgAVN. Full article

In vitro models of the human nasal cavity are crucial for understanding the deposition dynamics of nasally administered drugs. Three-dimensional (3D) printing offers a powerful method for creating patient-specific, anatomically precise models for such experimental purposes. Background/Objectives: This study details the complete workflow for the development, design, and fabrication of a sectioned nasal cavity model intended for droplet deposition analysis of nasal sprays. Methods: A digital nasal cavity model was derived from medical imaging data and optimized for computer-aided design (CAD) operations. It was segmented into five therapeutically relevant regions: nasal vestibule, olfactory area, middle and upper turbinates, lower turbinate, and nasopharynx. Sections were 3D-printed in polypropylene for chemical compatibility, and a carbon fiber-reinforced fixation frame ensured precise alignment and airtight assembly. Results: Functional validation confirmed the model’s functional relevance through comparative deposition studies using automated actuation and high-performance liquid chromatography (HPLC) based regional quantification. Two devices with distinct spray characteristics (characterized separately by laser diffraction, plume geometry, and spray pattern imaging) were tested under varied administration conditions. The study demonstrated the model’s ability to discriminate between products, establishing a solid foundation for future investigations incorporating additional variables. Conclusions: Overall, the developed methodology provides a cost-effective and replicable platform for producing anatomically accurate, sectioned nasal cavity models. The newly developed in vitro system is well suited for detailed, region-specific analysis of nasal spray deposition, offering a valuable tool for pharmaceutical research and development. Full article

The management of non-small cell lung cancer (NSCLC), including lung adenocarcinomas (LUAD), has been revolutionized with the advent of precision oncology. While advanced cancers often carry poor prognosis, those harboring specific molecular alterations sensitive to targeted therapy (notably tyrosine kinase inhibitor [TKI]) have experienced improved response to treatment and survival outcomes. Consequently, detecting these alterations through molecular screening panel has become standard in several countries, although this necessitates high-quality tissue sampling to inform optimal therapeutic decisions. Oncologic imaging occupies a pivotal role in the routine care of patients, in particular at diagnosis, with a wealth of information gathered but underutilized, as medical imaging reflects the disease in its entirety at a given time point. Moreover, recent advancements in imaging quantitative analysis, including radiomics and artificial intelligence, could aid in better integration and understanding of this information that has been overlooked for years. Several radiological phenotypes (or radiophenotypes) have been linked to tumor genomic alterations, both in standard radiology relying on semantic features and metastatic patterns, and in radiomics. Ultimately, understanding the relationships between imaging and targetable genomic alterations via accurate imaging biomarkers could complement ambiguous tumor or liquid biopsy, detect emerging new alterations, and even substitute biopsy through ‘virtual biopsy’. During the past decade, there has been a surge in research focused on radiogenomic assessment of NSCLC and especially LUAD. However, due to the low prevalence of many oncogenic drivers, the scientific literature may lack clarity or present conflicting findings. This comprehensive review aims to provide a summary of the current state of this research, offering insights into the complex interplay between imaging and genomic alterations in lung adenocarcinoma. Full article

Chronic rhinosinusitis (CRS) is a persistent inflammatory condition frequently associated with Staphylococcus aureus. The bacterium’s ability to evade immune clearance and establish long-term infection complicates treatment. In our previous study, we demonstrated that S. aureus isolates obtained from patients with CRS (CRS-S. aureus isolates; CSS) exhibit reduced glycolytic activity and cytotoxicity, which is consistent with a persistence-associated phenotype. Here, we present transcriptomic evidence that supports this shift. Comparative RNA sequencing of CSS and control (S. aureus isolates from healthy carriers, MIN) isolates from healthy individuals revealed significantly lower expression of genes involved in canonical virulence pathways in CSS isolates, particularly during the early growth phase. These profiles suggest reduced acute virulence in favour of metabolic changes that aid survival in the chronically inflamed sinus. The distinct transcriptional state of CSS isolates might reflect the influence of the CRS host milieu in shaping bacterial behaviour. Host factors such as sustained inflammation or altered nutrient availability may select for persistence-associated phenotypes. Together, these findings advance our understanding of chronic S. aureus infection and may aid/guide the development of therapies aimed at disrupting persistence programmes or enhancing host resilience. Full article

Polygonum cuspidatum, a traditional medicinal plant widely cultivated in Hubei Province, China, contains resveratrol, which has been shown to regulate lipoprotein metabolism, inhibit platelet aggregation, and aid in the prevention of arteriosclerosis and cardiovascular diseases. However, conventional extraction methods are often limited by low efficiency and solvent toxicity. A novel extraction strategy integrating an ultrasound-assisted extraction with natural deep eutectic solvents (NADES) was developed to achieve environmentally friendly and effective recovery of resveratrol from Polygonum cuspidatum. The optimized NADES system consisted of betaine and DL-malic acid in a 1:4 molar ratio with 50% water content. Using single-factor experiments and Response Surface Methodology, the following parameters were identified as optimum: solid–liquid ratio, 1:28 g/mL; ultrasonic power, 240 W; ultrasonic temperature, 40 °C; and ultrasonic time, 30 min. In such a case, the resveratrol yield reached 33.12 mg/g by UV-Vis spectroscopy and 2.95 mg/g by HPLC analysis, significantly higher than that obtained by other methods. Antioxidant assays demonstrated that the extract exhibited strong scavenging activity against ABTS⁺•, DPPH•, and •OH radicals. These results demonstrate that the ultrasound-assisted extraction with NADES method provides an efficient and eco-friendly alternative for extracting resveratrol from Polygonum cuspidatum, yielding extracts with notable antioxidant properties. Full article

Background: POP surgery improves anatomical support and quality of life, but urinary, bowel, sexual, and pain issues are common after surgery. The role of rehabilitation in addressing these problems is recognized, though not yet clearly defined. Objective: This scoping review aims to map the clinical evidence on conservative rehabilitation interventions for urinary, bowel, and sexual dysfunction, and pelvic pain after POP surgery. Methods: In accordance with PRISMA-ScR guidelines, we included randomized controlled trials, cohort studies, observational studies, and systematic reviews relevant to post-surgical rehabilitation options frequently encountered in clinical settings, including pelvic floor muscle training (PFMT), physiotherapy, and multimodal programs. Meta-analysis was not conducted due to clinical and methodological heterogeneity across the studies. Results: PFMT demonstrates beneficial effects on symptom severity and pelvic muscle function in women with POP. Postoperative rehabilitation may improve urinary continence, sexual function, and pelvic pain, although the strength of current evidence remains limited. Many studies prioritize surgical revision over conservative management, and the effectiveness of rehabilitation for persistent or de novo symptoms is not well established. Conclusions: Conservative rehabilitation, especially PFMT, may aid recovery and improve function after POP surgery. More research is needed to define the optimal protocols and to determine how to incorporate them into post-surgical care. Full article