Search Results (1,150)

Background: Cataract is a progressive lens opacity. According to the World Health Organization, about 45 million people in the world are blind, with about half of these cases attributable to cataracts. Due to the complexity of cataract disease, current research on cataracts is far from sufficient, so it is especially important to understand the development process and the pathogenic factors of cataracts. Myodes rufocanus (M. rufocanus) is an animal of the M. rufocanus of the hamster family Volinae. In developing M. rufocanus, we found an individual of M. rufocanus with a congenital cataract phenotype. We confirmed the symptoms of cataract under natural light and using a slit lamp. Methods: Therefore, we analyzed the mechanism of congenital cataract in M. rufocanus from the aspects of pathological histology, physiology and biochemistry, and gene level, aiming to explore the feasibility of its development into an animal model of cataract. Cataract is a progressive lens opacity and a leading cause of visual impairment. Understanding its pathogenesis requires appropriate animal models. In a laboratory-bred colony of M. rufocanus, we identified individuals with a spontaneous congenital cataract phenotype, confirmed by gross observation and slit lamp examination. To characterize this phenotype and explore its potential as an animal model, we performed pathological, physiological, biochemical, and transcriptomic analyses using three cataract-affected and three normal age-matched male individuals (8 weeks old per group). Results: Blood tests revealed significantly lower white blood cell and lymphocyte counts in the cataract group, while blood glucose and other biochemical parameters showed no significant differences. Histologically, cataractous lenses exhibited eosinophilic aggregation in the nuclear region with disorganized fiber cells. Transcriptome analysis identified 6544 differentially expressed genes, including downregulation of crystallin genes (CRYBB2, CRYBA4, CRYGS) known to be associated with congenital cataract. KEGG pathway enrichment analysis highlighted retinol metabolism, tyrosine metabolism, and cytochrome P450-related pathways. RT-qPCR confirmed reduced CRYBB2 expression in cataractous eyes. Conclusions: This study provides the first transcriptome dataset for M. rufocanus ocular tissues and offers preliminary evidence that this naturally occurring cataract phenotype may serve as a potential model for congenital cataract research. Full article

This study examines how the international harmonisation of intellectual property rules, particularly trade secret protection, reshapes the governance of artificial intelligence (AI) in ways that both enable and threaten justice. We argue that convergent standards on undisclosed information are essential for legal certainty in knowledge-intensive AI investments. Such standards are anchored in TRIPS, reinforced by WIPO guidance and digital trade agreements, and complemented by regional instruments such as the EU Trade Secrets Directive. This emerging framework facilitates cross-border technological cooperation while helping prevent the “regulatory expropriation” of code, models, and data infrastructures. At the same time, when this pro-secrecy architecture is extended to opaque algorithmic systems that mediate access to credit, employment, welfare, health and justice, it can entrench digital vulnerability: information asymmetries between firms, states and citizens; barriers to meaningful transparency and audit; and pathogenic forms of exclusion that disproportionately affect already disadvantaged groups. Building on the concept of digital and structural vulnerability, the paper defends a vulnerability-sensitive approach to harmonisation in which trade secret protection is balanced against human rights, algorithmic accountability and the regulatory space of Global South states. We conclude that only an intellectual property regime guided by an ethics and politics of vulnerability can reconcile economic integration, technological development and reducing digital vulnerability in deeply unequal societies. Full article

Background: Early detection and monitoring of enamel changes during caries lesion formation are essential for preventive management. This study aimed to evaluate time-dependent enamel demineralization using micro-computed tomography (micro-CT) and to compare its diagnostic performance with laser fluorescence and digital colorimetric image analysis. Methods: Twelve sound human permanent teeth were subjected to a gel-based lactic acid demineralization for 14 days. Assessments were performed at baseline and after 3, 7, and 14 days. Enamel mineral density (MD) and demineralization depth (DD) were measured using micro-CT. Laser fluorescence was evaluated using DIAGNOdent, while colorimetric changes were analyzed through standardized digital imaging using the CIE Lab* system, including ΔE and Whiteness Index (WI). Statistical analysis included repeated measures ANOVA and Pearson correlation (p < 0.05). Results: A significant time-dependent progression of enamel demineralization was observed. Demineralization depth increased from 0.0828 mm (3 days) to 0.234 mm (14 days) (p < 0.001), while mineral density decreased significantly over time (p < 0.001). DIAGNOdent values showed significant increases after 7 and 14 days (p = 0.002). Colorimetric analysis revealed early detectable changes, with ΔE exceeding clinically perceptible thresholds as early as day 3. WI values increased progressively, indicating enhanced enamel opacity. A weak but significant negative correlation between MD and DD was found (p = 0.04). Conclusions: Enamel demineralization progresses in a time-dependent manner and can be effectively monitored using micro-CT, laser fluorescence, and colorimetric analysis. Digital colorimetric analysis may serve as a valuable adjunctive tool in caries diagnostics. Full article

Epistemology remains tacitly anthropocentric: it treats knowledge as something produced and validated through human cognitive capacities such as understanding, intuition, and transparent justification. Yet contemporary science and artificial intelligence increasingly depend on non-human systems that generate mathematically valid results, empirically successful models, and operationally reliable inferences that no human can fully survey or interpret. This article develops xenoepistemics, a structural theory of non-anthropocentric knowledge. The central claim is that epistemic evaluation must be reformulated in terms of system-level properties—reliability, robustness, counterfactual sensitivity, and domain transfer—rather than mentalistic notions such as belief or understanding. I offer (i) a definition of xenoepistemic systems as systems that track structure in a target domain without requiring human-style semantic access; (ii) a minimal account of epistemic agency without minds that avoids trivialization; and (iii) a non-circular trust framework that distinguishes empirical success from epistemic legitimacy using independent validation regimes. This paper addresses a reflexive worry—that a human-authored theory cannot dethrone human epistemology—by separating standpoint from object: xenoepistemics is articulated by humans but is not about human cognition. I discuss the pragmatic value of xenoepistemic knowledge production, the limits of independent verification for opaque systems, domain-relative thresholds for xenoepistemic authority, and the problem of constitutionally human-inaccessible knowledge. Finally, I diagnose and formalize the Marcusian regress paradox: recurrent goalpost-shifting, whereby every machine competence is reclassified as irrelevant once achieved. Xenoepistemics reframes this debate by treating non-human knowledge as a present reality requiring new norms, not as a future curiosity. Full article

Objective: To develop and validate an artificial intelligence (AI) system for automated lens opacities classification system III (LOCS III)-based grading of all three major cataract subtypes using anterior segment optical coherence tomography (AS-OCT). Methods: This is a single-center cross-sectional study. AS-OCT images were collected and manually graded by ophthalmologists according to LOCS III. The dataset was randomly split into training, validation, and test sets. We propose a novel multi-granularity mask-guided network (MMNet) that jointly performs lens substructure segmentation and severity grading. The model’s performance was assessed on an independent test set for automatic grading of cortical cataract (CC), nuclear cataract (NC), and posterior subcapsular cataract (PSC) and the grading performance of the proposed method against ophthalmologists was also evaluated. The model’s interpretability was assessed via attention heatmaps and feature visualization. Results: The proposed MMNet exhibited high agreement with ground truth conducted through gold standard. The proportions of predictions with an absolute error < 1.0 for three subtypes range from 83.02% to 89.94%. The model’s grading accuracy for cataract subtypes was between 82.20 ± 1.41% and 89.76 ± 1.31% among the three subtypes, the Area Under the Curve (AUC) was between 0.954 (95% CI, 0.952–0.969; p < 0.001) and 0.973 (95% CI, 0.964–0.985; p < 0.001). The MMNet shows a satisfactory mean absolute error (MAE) of 0.14 ± 0.35 in CC, 0.10 ± 0.30 in NC, and 0.17 ± 0.38 in PSC grading. It also achieved a fast grading speed of 0.0178 s/image against manual grading. Conclusions: The proposed AI model presented advanced performance on AS-OCT images in automated LOCS III-based cataract grading for CC and NC, and also showed feasibility in PSC assessment. Full article

The integration of generative artificial intelligence (GAI) into digital learning environments is a profound socio-technical transformation. While GAI promises enhanced accessibility and efficiency, it simultaneously obscures the human creativity and intellectual labour that underpins digital knowledge production. This opacity limits creators’ visibility into how their work is used, evaluated, and monetised. This review application work investigates how several leading large language models, including ChatGPT (GPT-4o), Gemini (1.5 Flash), and DeepSeek (V3), interact with a creative platform hosting over 300 original essays, poems, and artworks from various human creatives. Our review reveals that despite clear evidence of models engaging with original materials, standard platform analytics of the average creative record no attribution, referrals, or traceable interaction from their end, rendering creators’ labour invisible. This compels critical examination of knowledge provenance and power within AI-mediated education. To address this, we propose a socio-technical framework, Chujoyi-TraceNet, not as a technical fix, but a mechanism to re-centre ethics, justice, and recognition in digital governance. By integrating real-time tracking, blockchain-enabled licensing, and metadata watermarking, Chujoyi-TraceNet operationalises the principles of equitable attribution. This study argues for a re-imagining of digital ecosystems in education, one that links the technical act of attribution to broader debates on digital labour, platform ethics, and the pursuit of social justice, thereby contributing to more democratic and accountable learning media in the era of Industry 4.0 and 5.0. Full article

As a leading method for Novel View Synthesis (NVS), 3D Gaussian Splatting (3DGS) faces limitations. Fixed thresholds governing Gaussian scale and opacity lead to over-reconstruction or under-reconstruction, while the linear penalty used for handling outliers during optimization tends to introduce artifacts. Therefore, we propose Adaptive 3DGS featuring a dynamic deletion mechanism. Specifically, our method calculates coverage for each Gaussian based on its scale during removal. Gaussians with high coverage face stricter scale thresholds to reduce over-reconstruction, while those with lower coverage receive lenient thresholds to preserve details. Simultaneously, transparency-based contribution assessment is applied. Gaussians with low contribution meet stricter transparency thresholds to combat over-reconstruction, while high-contribution ones get lenient thresholds to mitigate under-reconstruction. During optimization, introducing Huber loss promotes quadratic growth for small errors, reducing smoothing to alleviate artifacts and better preserve details. Evaluation on standard datasets shows our method improves peak signal-to-noise ratio (PSNR) by 0.3 dB over 3DGS and 0.5 dB over MS-3DGS at 4× resolution, and it achieves a 0.1 dB gain over Mip-Splatting, confirming its effectiveness and robustness. Full article

Corneal alkali burns represent one of the most severe forms of ocular surface injury and frequently result in persistent inflammation, corneal neovascularization, stromal remodeling, and permanent visual impairment. Current therapeutic approaches incompletely control the inflammatory mechanisms that sustain pathological angiogenesis and tissue disorganization. In this study, we evaluated the effects of a transglutaminase-binding fusion protein (FP) in a rat model of alkali-induced corneal injury. Following standardized alkali burns, animals were treated topically with FP, secretory leukocyte protease inhibitor (SLPI), or Buffer. Corneal epithelial healing, opacity, and neovascularization were assessed clinically and by digital image-based quantification, while histological and immunofluorescence analyses were used to evaluate stromal organization and vascular invasion. Molecular mechanisms were investigated by RT-qPCR and Western blot analysis of key inflammatory, angiogenic, and signaling mediators. FP treatment significantly accelerated corneal re-epithelialization, reduced corneal opacity, and markedly attenuated corneal neovascularization compared to SLPI and Buffer controls. These effects were associated with coordinated downregulation of pro-inflammatory cytokines and angiogenic mediators, including TNF-α, IL-17, VEGF, and cPLA₂. Notably, FP suppressed transglutaminase 2 expression and induced early and sustained downregulation of NF-κB pathway components, identifying modulation of an upstream inflammatory pathway central to corneal angiogenesis and stromal remodeling. Collectively, these findings demonstrate that FP effectively limits inflammation-driven corneal neovascularization and tissue remodeling following alkali injury, supporting its potential as a disease-modifying therapeutic strategy for inflammatory ocular surface disorders. Full article

Pulmonary disease caused by nontuberculous mycobacteria represents an important diagnostic challenge, particularly in immunocompromised patients, in whom clinical and radiologic findings may mimic malignancy. We report the case of a 70-year-old woman with myelofibrosis treated with ruxolitinib who developed a tumor-like lesion in the left upper lobe on computed tomography, highly suggestive of lung cancer. Despite broad-spectrum antibiotic therapy, the lesion persisted; bronchoscopy did not yield diagnostic findings, and CT-guided transthoracic biopsy demonstrated necrotizing granulomatous inflammation without evidence of malignancy. Microbiological analysis subsequently identified Mycobacterium avium, and targeted antimycobacterial therapy led to clinical and radiologic improvement. This case highlights that pulmonary nontuberculous mycobacterial infection may present as a pseudotumoral lesion and should be considered in the differential diagnosis of mass-like pulmonary opacities, particularly in patients receiving Janus kinase inhibitor therapy. Full article

The decarbonization of marine transport requires the wider use of alternative low-carbon fuels that can be applied in existing compression ignition (CI) engines without major modifications. Hydrotreated vegetable oil (HVO) is considered a promising renewable drop-in fuel due to its favorable physicochemical properties and high cetane number. This study investigates the influence of neat HVO and its blends with conventional diesel fuel on the combustion characteristics, energy, and emission indicators of a CI engine operating under different load conditions and exhaust gas recirculation (EGR) ratios. Experimental tests were carried out on a four-cylinder CI engine at constant speed and variable load using diesel fuel (D100), HVO100, and their blends (D80_HVO20 and D50_HVO50). In-cylinder pressure measurements and combustion analysis were performed using AVL instrumentation and AVL BOOST software. The results show that increasing the HVO fraction slightly advances combustion phasing and increases maximum in-cylinder pressure by approximately 4–5%. The use of HVO was found to reduce brake-specific fuel consumption by up to 3.4% and increase brake thermal efficiency by about 1.9%, although volumetric fuel consumption increases due to the lower fuel density. In addition, higher HVO content significantly reduces smoke opacity by up to 42% and decreases CO₂ emissions by 4.7–6.3%, while the influence on NO_x emissions depends on the applied EGR strategy. The results indicate that HVO and its blends can be effectively applied in CI engines; however, optimal performance and emission characteristics require appropriate calibration of EGR rate and fuel injection timing. Full article

Background: Artificial intelligence (AI) is transforming leadership and raising critical questions about decision-making, leadership capabilities, and ethical accountability in increasingly digitalized organizations. Objective: This systematic review synthesizes peer-reviewed evidence to answer: How does AI integration transform leadership and decision-making in organizations? Methods: A PRISMA 2020-compliant systematic review was conducted using structured Boolean searches in Scopus and Web of Science Core Collection on 26 February 2026. Eligibility was restricted to English-language, peer-reviewed, open-access journal articles with an explicit AI–leadership integration signal. Records were deduplicated and screened by two reviewers, with full-text assessment conducted against predefined criteria. A qualitative, narrative (conceptual) synthesis integrated heterogeneous empirical and conceptual contributions. Results: From 452 records, 84 studies met inclusion criteria. The synthesis identified three recurring analytical dimensions: (i) AI-augmented decision-making, (ii) leadership competencies and role shifts, and (iii) ethical challenges (accountability, transparency/opacity, fairness, privacy, and human agency). Integrating these dimensions, the review conceptualizes AI-driven leadership as a hybrid decision phenomenon in which AI accelerates and expands decision cycles, leaders reconfigure roles toward decision architecture and orchestration, and ethical conditions shape legitimacy, adoption, and authority dynamics. Conclusions: The review advances theory by specifying a mechanism-oriented model of AI-driven leadership and proposing testable propositions linking AI modality, role reconfiguration, and ethically conditioned legitimacy under key boundary conditions (e.g., sectoral stakes, governance capacity, and data/infrastructure readiness). Practically, it outlines an implementation pathway emphasizing decision criticality assessment, formalized human–AI task allocation, and institutionalized oversight mechanisms. Limitations: Findings are bounded by database selection and the open-access full-text constraint, which may under-represent paywalled scholarship. Full article

COVID-19 still poses a global public health challenge, exerting pressure on radiology services. Chest X-ray (CXR) imaging is widely used for respiratory assessment due to its accessibility and cost-effectiveness. However, its interpretation is often challenging because of subtle radiographic features and inter-observer variability. Although recent deep learning (DL) approaches have shown strong performance in automated CXR classification, their black-box nature limits interpretability. This study proposes an explainable deep learning framework for COVID-19 detection from chest X-ray images. The framework incorporates anatomically guided preprocessing, including lung-region isolation, contrast-limited adaptive histogram equalization (CLAHE), bone suppression, and feature enhancement. A novel four-channel input representation was constructed by combining lung-isolated soft-tissue images with frequency-domain opacity maps, vessel enhancement maps, and texture-based features. Classification was performed using a modified Xception-based convolutional neural network, while Gradient-weighted Class Activation Mapping (Grad-CAM) was employed to provide visual explanations and enhance interpretability. The framework was evaluated on the publicly available COVID-19 Radiography Database, achieving an accuracy of 95.3%, an AUC of 0.983, and a Matthews Correlation Coefficient of approximately 0.83. Threshold optimisation improved sensitivity, reducing missed COVID-19 cases while maintaining high overall performance. Explainability analysis showed that model attention was primarily focused on clinically relevant lung regions. Full article

Corneal fibrosis, clinically referred to as corneal scarring, disrupts the normal architecture and transparency of the cornea and remains a major cause of visual impairment worldwide. Although corneal transplantation can restore vision, its effectiveness is constrained by limited accessibility, donor tissue shortages, and the risk of allograft rejection. Treatments with human corneal stromal stem cells (hCSSCs) have demonstrated scarless healing in preclinical models of acute corneal injury. Here, we report that hCSSCs also modulated pre-existing corneal opacities. We established a reproducible in vivo model of chronic corneal opacity. Given that scar severity varies among corneas even after identical injuries, we developed a non-invasive, image-based method to quantify opacity volume longitudinally in individual corneas. Using this approach, we evaluated the scar-reducing potential of three hCSSC batches previously shown to inhibit acute scarring. Following cell treatment, the pre-existing opacity volumes gradually decreased. In vitro, hCSSCs exposed to pro-inflammatory stimulus exhibited increased metalloproteinase (MMP) activity relative to tissue inhibitor of metalloproteinase (TIMP), as indicated by an elevated MMP2/TIMP2 ratio. This shift may promote matrix remodeling and scar resolution. Overall, our findings provide proof-of-concept for hCSSC-based therapy as a strategy to reduce established corneal scarring and restore corneal transparency. Full article

This research focuses on developing bioplastic films using agrifood industrial waste, which included starch from avocado seed, cellulose from cornstalk, carrot and beet peel, and pulp from a food company in México. The films were produced with a matrix of gelatin and glycerol, and different formulations of starch and cellulose. The films were characterized and tested as wrappers of Manchego cheese. The films containing starch are transparent; films with cellulose showed opacity and paper-like structure. Films containing starch–cornstalk cellulose showed the highest hydrophobic properties. In turn, films with carrot cellulose had the highest plastic properties with high elongation capacity and the lowest Young modules; films with starch and other celluloses showed the opposite data. The highest thermal capacity was observed in films containing cellulose from cornstalks and beet waste. In turn, the highest temperatures of transition, crystallization, and melting were registered in films containing starch. Films with starch and cellulose served well as wrappers of Manchego cheese, conserving 92% of the weight of cheese after 21 days of storage at 4 °C. All films were biodegradable in compost after 10 days, and they were degradable by physicochemical factors after 40 days. Full article

Background and Clinical Significance: Acetazolamide is routinely used post-cataract surgery to prevent intraocular pressure (IOP) spikes. Rare non-cardiogenic pulmonary edema (NCPE) cases highlight its risks in elderly comorbid patients. This report details acetazolamide-induced NCPE and provides a review of current evidence from the literature. Case Presentation: A 74-year-old male with chronic kidney disease, atrial fibrillation, and aortic aneurysm repair received 250 mg oral acetazolamide post-cataract extraction. Clinical, imaging, and lab data were documented during Intensive Care Unit (ICU) stay. PubMed/Google Scholar review identified similar cases. Within 30 min, severe hypoxemia with SpO₂ (peripheral oxygen saturation) of 77%, accompanied by tachypnea and hypertension, necessitated endotracheal intubation. Echocardiography showed preserved left ventricular (LV) function; computed tomography (CT) confirmed bilateral alveolar opacities without cardiomegaly or embolism, indicating permeability-mediated NCPE. Lung-protective mechanical ventilation and vasopressor therapy resulted in hemodynamic and respiratory stabilization. On day 4, ventilator-associated pneumonia (VAP) due to Acinetobacter baumannii resolved with targeted antibiotic therapy. The patient made a full recovery following ICU discharge. To date, nine prior cases have been reported, alongside 31 entries in EudraVigilance reflecting a 19.4% mortality rate. Conclusions: Rapid-onset NCPE from acetazolamide involves endothelial injury, distinct from cardiogenic pulmonary edema. Early recognition, drug cessation, and admission to the intensive care unit (ICU) are vital components of therapeutic intervention. Risk stratification and pharmacovigilance are recommended for perioperative safety. Full article