Search Results (22)

Corneal diseases affect a significant proportion of the global population, with younger age groups being particularly vulnerable. In severe cases involving vision loss, standard techniques such as keratoplasty often fail. These cases require more invasive treatment through the implantation of artificial cornea or keratoprostheses. Since the development of the oldest technique for creating and implanting the first keratoprostheses by Strampelli, these devices have experienced major modifications to improve their biocompatibility, function, and long-term viability. As a result, there is currently a wide range of implants and procedures that are available and can be applied according to patient indications and clinical settings. This narrative review attempts to cover the literature on this topic by focusing on (1) recent advances in rigid (Boston Type I and II, osteo-odonto-keratoprosthesis, modified osteo-odonto-keratoprosthesis, and LV Prasad Eye Institute keratoprosthesis) and soft (AlphaCor, CorNeat, and EndoArt) keratoprosthesis designs and (2) more recent studies on innovative biomaterials and techniques that could lead to the fabrication of fully functional biosynthetic corneas with optimal properties. In our review of these materials, we cover the current clinical applications and limitations, as well as future prospects of less invasive and more efficient prostheses that could improve patient outcomes and quality of life. Full article

Endometriosis (ENDO) and poor ovarian response (POR) represent challenging conditions in assisted reproduction. Both, associated with altered follicular fluid (FF) composition, specifically impact on granulosa cell (GC) function in an incompletely understood way. GCs from male factor (MF, n = 30), ENDO (n = 38), and POR (n = 27) patients were cultured in media supplemented with FF from each group (FF-MF, FF-ENDO, FF-POR). Proliferation, morphology, and secretory activity (cortisol, estradiol, progesterone, IL-6) were assessed. GC proliferation depended primarily on FF origin, being highest with FF-ENDO, intermediate with FF-POR, and lowest with FF-MF. Morphological analysis revealed enrichment of muscle-like and fibroblast-like morphologies under FF-ENDO and FF-POR, suggestive of dysregulated luteinization and extracellular matrix remodeling. Secretory activity reflected a complex interplay between GC origin and FF type: IL-6 was strongly induced by FF-MF and FF-POR but consistently suppressed by FF-ENDO; cortisol and estradiol were generally consumed, while progesterone synthesis was largely confined to MF-GCs, with only variable induction in ENDO-GCs exposed to FF-POR. These findings indicate that pathological FF milieus reprogram GC behavior in distinct ways, with potential consequences for luteal function and oocyte competence. Identifying the molecular mediators of these alterations may guide tailored strategies to improve ART outcomes in ENDO and POR patients. Full article

Purpose: Gastrointestinal (GI) illness demands precise and efficient diagnostics, yet conventional approaches (e.g., endoscopy and histopathology) are time-consuming and prone to reader variability. This work presents GID-Xpert, a deep learning framework designed to improve feature learning, accuracy, and interpretability for GI disease classification. Methods: GID-Xpert integrates a hierarchical, multi-stage attention-driven mixture of experts with dynamic routing. The architecture couples spatial–channel attention mechanisms with specialized expert blocks; a routing module adaptively selects expert paths to enhance representation quality and reduce redundancy. The model is trained and evaluated on three benchmark datasets—WCEBleedGen, GastroEndoNet, and the King Abdulaziz University Hospital Capsule (KAUHC) dataset. Comparative experiments against state-of-the-art baselines and ablation studies (removing attention, expert blocks, and routing) are conducted to quantify the contribution of each component. Results: GID-Xpert achieves superior performance with 100% accuracy on WCEBleedGen, 99.98% on KAUHC, and 75.32% on GastroEndoNet. Comparative evaluations show consistent improvements over contemporary models, while ablations confirm the additive benefits of spatial–channel attention, expert specialization, and dynamic routing. The design also yields reduced computational cost and improved explanation quality via attention-driven reasoning. Conclusion: By unifying attention, expert specialization, and dynamic routing, GID-Xpert delivers accurate, computationally efficient, and more interpretable GI disease classification. These findings support GID-Xpert as a credible diagnostic aid and a strong foundation for future extensions toward broader GI pathologies and clinical integration. Full article

Accurate segmentation of surgical instruments in endoscopic videos is crucial for robot-assisted surgery and intraoperative analysis. This paper presents a Segment-then-Classify framework that decouples mask generation from semantic classification to enhance spatial completeness and temporal stability. First, a Mask2Former-based segmentation backbone generates class-agnostic instance masks and region features. Then, a bounding box-guided instance-level spatiotemporal modeling module fuses geometric priors and temporal consistency through a lightweight transformer encoder. This design improves interpretability and robustness under occlusion and motion blur. Experiments on the EndoVis 2017 and 2018 datasets demonstrate that our framework achieves mIoU improvements of 3.06%, 2.99%, and 1.67% and mcIoU gains of 2.36%, 2.85%, and 6.06%, respectively, over previously state-of-the-art methods, while maintaining computational efficiency. Full article

Purpose: This study aimed to refine the criteria for EndoART implantation regarding posterior corneal irregularity; to improve the selection of candidates for this synthetic alternative to endothelial keratoplasty. Methods: This study analyzed the impact of posterior corneal surface elevation differences; anterior chamber depth (ACD); and preoperative corneal pachymetry on the success of EndoART implant adhesion. Patients undergoing EndoART implantation at the Medical University of Vienna were assessed using OCT to measure corneal irregularities. Postoperative outcomes, including re-bubbling rates; implant adhesion; and visual acuity changes, were monitored. Results: EndoART successfully adhered in eyes with moderate posterior irregularities (elevation differences up to 204 µm). Severe irregularities (elevation differences > 200 µm) resulted in implant detachment. No significant correlation was found between corneal pachymetry or ACD and adhesion failure. Glaucoma devices and prior penetrating keratoplasty did not significantly affect adhesion. Some cases required re-bubbling, and patients reported pain reduction and moderate improvements in visual acuity. Conclusions: This study found that EndoART implantation can be successful despite posterior corneal irregularity. EndoART represents a viable solution for patients with poor biological graft survival prognosis, including those with glaucoma or prior surgeries, expanding its potential use and addressing the global donor cornea shortage. Full article

Endometriosis is a complicated condition characterized by inflammation, low oocyte quality, and decreased uterus receptivity, associated with fertility issues. This study aims to better understand the reduced pregnancy outcome in endometriosis by analyzing both the granulosa cells (GCs) and the follicular fluids (FFs) obtained during the assisted reproductive technology (ART)-related oocyte pick-up. Seventy patients, approaching our ART Center with the diagnosis of infertility for Age-Idiopathic Factor (AIF) (n = 36), endometriosis (ENDO) (n = 23), or male factor (MF) (n = 11), were enrolled in this study. GCs from each group were separately analyzed for morphology, replication, and expression of Connexin-43 and Follicle-Stimulating Hormone Receptor (FSHR) by microscopy, flow cytometry, and immunocytochemistry. Results show that FF in a culture medium allowed GCs to survive and replicate. Upon culturing GCs from each group with ENDO follicular fluid, increases were observed in both population doublings and in the development of fibroblast-like and muscle-like morphologies. Despite undergoing morphological changes, GCs consistently expressed FSHR. However, exposure to ENDO follicular fluid led to an upregulation of Connexin-43 expression across all GC groups. These findings suggest that in endometriosis, FF contains unidentified factors that can induce aberrant replication, morphological differentiation, and overexpression of Connexin-43, potentially contributing to follicular dysfunction. Full article

Portal hypertension (PH) is a complication of advanced liver diseases, including cirrhosis and hepatocellular carcinoma, often leading to unfavorable outcomes. Endo-hepatology, particularly endoscopic ultrasound (EUS) has revolutionized the assessment of PH. Notably, EUS-guided portal pressure gradient (EUS-PPG) enables measurement of portal and hepatic venous pressures, offering diagnostic precision for both cirrhotic and non-cirrhotic forms of PH, including porto-sinusoidal vascular disorder (PSVD). EUS-based assessment of PH in advanced liver disease can refine diagnostic workup and prognostication, supporting therapeutic decisions. Additionally, EUS-guided liver biopsy (EUS-LB) achieves high-quality histological samples with fewer complications compared to percutaneous techniques, enabling thorough evaluation of chronic liver diseases and vascular abnormalities. EUS-shear wave elastography (EUS-SWE) further refines stiffness measurements where standard imaging fails. Moreover, EUS plays a major role in controlling variceal hemorrhage, a severe PH complication. EUS-guided coil and cyanoacrylate injection for gastric varices demonstrate a great efficacy, often surpassing conventional endoscopy. Similarly, EUS-based identification and treatment of perforator vessels feeding esophageal varices reduce rebleeding risks, particularly in challenging patients. The combination of these state-of-the-art interventions supports a “one-stop strategy”, integrating variceal screening, biopsy, and portal pressure measurement within a single procedure. Despite these advancements, refinements in sedation protocols, patient selection, and cost-effectiveness data are necessary. While noninvasive tools remain central in guidelines, EUS-based methods continue to expand their role, especially in complex cases. This review summarizes the applications and impact of EUS in evaluating PH, emphasizing its importance in contemporary hepatology and its potential as a pivotal diagnostic modality in cirrhosis complicated by PH. Full article

The advancement of neural radiance fields (NeRFs) has facilitated the high-quality 3D reconstruction of complex scenes. However, for most NeRFs, reconstructing 3D tissues from endoscopy images poses significant challenges due to the occlusion of soft tissue regions by invalid pixels, deformations in soft tissue, and poor image quality, which severely limits their application in endoscopic scenarios. To address the above issues, we propose a novel framework to reconstruct high-fidelity soft tissue scenes from low-quality endoscopic images. We first construct an EndoTissue dataset of soft tissue regions in endoscopic images and fine-tune the Segment Anything Model (SAM) based on EndoTissue to obtain a potent segmentation network. Given a sequence of monocular endoscopic images, this segmentation network can quickly obtain the tissue mask images. Additionally, we incorporate tissue masks into a dynamic scene reconstruction method called Tensor4D to effectively guide the reconstruction of 3D deformable soft tissues. Finally, we propose adopting the image enhancement model EDAU-Net to improve the quality of the rendered views. The experimental results show that our method can effectively focus on the soft tissue regions in the image, achieving higher fidelity in detail and geometric structural integrity in reconstruction compared to state-of-the-art algorithms. Feedback from the user study indicates high participant scores for our method. Full article

Background/Objectives: The objective of this study was to examine the morphological corneal changes and outcomes following the implantation of an artificial endothelial layer (EndoArt) in patients with chronic corneal oedema. Methods: A systematic review of the literature was conducted alongside a detailed analysis of two clinical cases with chronic corneal oedema that were treated using EndoArt. Our experience with these two cases is included to provide practical insights and real-world outcomes. Results: Across the 24 cases reported (including the two presented here), an analysis was possible in 23 cases. Notably, 82% of patients had undergone at least one previous corneal transplant, with 39% having undergone three or more transplants. Additionally, 78% of cases had ocular comorbidities, with glaucoma surgery being the most prevalent (83%), which could have impacted visual outcomes. The follow-up period ranged from 3 to 17 months with a median of 3 months. After EndoArt implantation, the average reduction in the central corneal thickness (CCT) was 29%, and the rebubbling rate was 47.8%, with some cases requiring no rebubbling, while others required it up to 100% of the time. Visual acuity significantly improved from a mean best-corrected visual acuity (BCVA) value of 1.61 ± 0.5 logMAR to 1.07 ± 0.59 logMAR (p < 0.001). The CCT decreased from 771 ± 146 µm to 580 ± 134 µm (p < 0.001). These findings are consistent with our experience. Conclusions: EndoArt shows promise as an alternative treatment for chronic corneal oedema in complex cases where conventional corneal transplantation has failed or carries a high risk of failure. The morphological changes observed using anterior segment optical coherence tomography (OCT) and in vivo confocal microscopy (IVCM) were similar to those reported after endothelial keratoplasty, with the notable exception of the absence of the hyper-reflective donor–host interface. Full article

Recent advances in deep learning have shown significant potential for accurate cell detection via density map regression using point annotations. However, existing deep learning models often struggle with multi-scale feature extraction and integration in complex histopathological images. Moreover, in multi-class cell detection scenarios, current density map regression methods typically predict each cell type independently, failing to consider the spatial distribution priors of different cell types. To address these challenges, we propose CellRegNet, a novel deep learning model for cell detection using point annotations. CellRegNet integrates a hybrid CNN/Transformer architecture with innovative feature refinement and selection mechanisms, addressing the need for effective multi-scale feature extraction and integration. Additionally, we introduce a contrastive regularization loss that models the mutual exclusiveness prior in multi-class cell detection cases. Extensive experiments on three histopathological image datasets demonstrate that CellRegNet outperforms existing state-of-the-art methods for cell detection using point annotations, with F1-scores of 86.38% on BCData (breast cancer), 85.56% on EndoNuke (endometrial tissue) and 93.90% on MBM (bone marrow cells), respectively. These results highlight CellRegNet’s potential to enhance the accuracy and reliability of cell detection in digital pathology. Full article

Background and Aims: Accurate recognition of endoscopic instruments facilitates quantitative evaluation and quality control of endoscopic procedures. However, no relevant research has been reported. In this study, we aimed to develop a computer-assisted system, EndoAdd, for automated endoscopic surgical video analysis based on our dataset of endoscopic instrument images. Methods: Large training and validation datasets containing 45,143 images of 10 different endoscopic instruments and a test dataset of 18,375 images collected from several medical centers were used in this research. Annotated image frames were used to train the state-of-the-art object detection model, YOLO-v5, to identify the instruments. Based on the frame-level prediction results, we further developed a hidden Markov model to perform video analysis and generate heatmaps to summarize the videos. Results: EndoAdd achieved high accuracy (>97%) on the test dataset for all 10 endoscopic instrument types. The mean average accuracy, precision, recall, and F1-score were 99.1%, 92.0%, 88.8%, and 89.3%, respectively. The area under the curve values exceeded 0.94 for all instrument types. Heatmaps of endoscopic procedures were generated for both retrospective and real-time analyses. Conclusions: We successfully developed an automated endoscopic video analysis system, EndoAdd, which supports retrospective assessment and real-time monitoring. It can be used for data analysis and quality control of endoscopic procedures in clinical practice. Full article

The paper provides a commentary on the theme of “Current and Future Trends in Tribological Research: Fundamentals and Applications”, which is a special feature issue commemorating the 10th anniversary of the journal, Lubricants. A historical discourse is provided regarding various aspects of tribology as a multi-disciplinary subject that interacts in an inter-disciplinary manner with many other subjects: multi-body dynamics, thermofluids and heat transfer, contact mechanics, surface science, chemistry, rheology, data science, and biology, to name but a few. Such interactions lead to many important topics including propulsion with different sources of energy, mitigating emissions, palliation of friction, enhancing durability and sustainability, optimization through detailed analysis, and the use of artificial intelligence. Additionally, issues concerning kinetics at various physical scales (from macroscale to microscale onto mesoscale and nanoscale) affecting the kinematics of contacts are discussed. The broad range of considered applications includes vehicular powertrains, rotor bearings, electrical machines, mammalian endo-articular joints, nanobiological attachment/detachment, and locomotion. Current state-of-the-art tribological research is highlighted within a multi-physics, multi-scale framework, an approach not hitherto reported in the open literature. Full article

The early diagnosis of cardiovascular diseases (CVDs) can effectively prevent them from worsening. The source of the disease can be effectively detected through analysis with cardiac magnetic resonance imaging (CMRI). The segmentation of the left ventricle (LV) in CMRI images plays an indispensable role in the diagnosis of CVDs. However, the automated segmentation of LV is a challenging task, as it is confused with neighboring regions in the cardiac MRI. Deep learning models are effective in performing such complex segmentation because of the high performing convolutional neural networks (CNN). However, since segmentation using CNN involves the pixel-level classification of the image, it lacks the contextual information that is highly desirable in analyzing medical images. In this research, we propose a modified U-Net model to accurately segment the LV using context-enabled segmentation. The proposed model achieves the automatic segmentation and quantitative assessment of LV. The proposed model achieves the state-of-the-art accuracy by effectively utilizing various hyperparameters, such as batch size, batch normalization, activation function, loss function and dropout. Our method demonstrated a statistical significance in the endo- and epicardial walls with a dice score of 0.96 and 0.93, respectively, an average perpendicular distance of 1.73 and percentage of good contours of 96.22 were achieved. Furthermore, a high positive correlation of 0.98 between the clinical parameters, such as ejection fraction, end diastolic volume (EDV), end systolic volume (ESV) and gold standard was obtained. Full article

NAD⁺ and ADP-ribose (ADPr)-containing molecules are at the interface of virus–host conflicts across life encompassing RNA processing, restriction, lysogeny/dormancy and functional hijacking. We objectively defined the central components of the NAD⁺–ADPr networks involved in these conflicts and systematically surveyed 21,191 completely sequenced viral proteomes representative of all publicly available branches of the viral world to reconstruct a comprehensive picture of the viral NAD⁺–ADPr systems. These systems have been widely and repeatedly exploited by positive-strand RNA and DNA viruses, especially those with larger genomes and more intricate life-history strategies. We present evidence that ADP-ribosyltransferases (ARTs), ADPr-targeting Macro, NADAR and Nudix proteins are frequently packaged into virions, particularly in phages with contractile tails (Myoviruses), and deployed during infection to modify host macromolecules and counter NAD⁺-derived signals involved in viral restriction. Genes encoding NAD⁺–ADPr-utilizing domains were repeatedly exchanged between distantly related viruses, hosts and endo-parasites/symbionts, suggesting selection for them across the virus world. Contextual analysis indicates that the bacteriophage versions of ADPr-targeting domains are more likely to counter soluble ADPr derivatives, while the eukaryotic RNA viral versions might prefer macromolecular ADPr adducts. Finally, we also use comparative genomics to predict host systems involved in countering viral ADP ribosylation of host molecules. Full article

Arenaza Cave is located in Vizcaya (N Spain) and contains important Palaeolithic rock art representations. This cave belongs to an active karstic system developed on Lower Cretaceous limestones, mainly consisting of micrites and biomicrites with abundant pyrite moulds. The paintings are made directly on the host rock or on thin stalagmitic calcite crusts. Cretaceous limestones in this area contain important iron ore deposits, which have been mined by subsurface and surface-mining methods since the beginning of the 20th century. Mining activities have induced significant changes in the karstic drainage pattern and in the endo and exokarstic morphologies of the Arenaza karstic system, directly affecting the state of conservation of the prehistoric paintings. Thus, in addition to natural process of deterioration, the enlargement of the limestone fissure system as a result of blasting-induced vibrations seems to be the responsible for changes in the rates of water-rock interactions and of the formation of botryoidal gypsum concretions on the rock surface. The final result is the activation and acceleration of detachment processes and the increase of irreversible deterioration processes in the cave. Full article