Osteoporosis is the systematic degeneration of the human skeleton, with consequences ranging from a reduced quality of life to mortality. Therefore, the prediction of osteoporosis reduces risks and supports patients in taking precautions. Deep-learning and specific models achieve highly accurate results using different imaging modalities. The primary purpose of this research was to develop unimodal and multimodal deep-learning-based diagnostic models to predict bone mineral loss of the lumbar vertebrae using magnetic resonance (MR) and computed tomography (CT) imaging. Patients who received both lumbar dual-energy X-ray absorptiometry (DEXA) and MRI (n = 120) or CT (n = 100) examinations were included in this study. Unimodal and multimodal convolutional neural networks (CNNs) with dual blocks were proposed to predict osteoporosis using lumbar vertebrae MR and CT examinations in separate and combined datasets. Bone mineral density values obtained by DEXA were used as reference data. The proposed models were compared with a CNN model and six benchmark pre-trained deep-learning models. The proposed unimodal model obtained 96.54%, 98.84%, and 96.76% balanced accuracy for MRI, CT, and combined datasets, respectively, while the multimodal model achieved 98.90% balanced accuracy in 5-fold cross-validation experiments. Furthermore, the models obtained 95.68%-97.91% accuracy with a hold-out validation dataset. In addition, comparative experiments demonstrated that the proposed models yielded superior results by providing more effective feature extraction in dual blocks to predict osteoporosis. This study demonstrated that osteoporosis was accurately predicted by the proposed models using both MR and CT images, and a multimodal approach improved the prediction of osteoporosis. With further research involving prospective studies with a larger number of patients, there may be an opportunity to implement these technologies into clinical practice.

Glaucoma is extensively treated with topical eye drops containing drugs. However, the retention time of the loaded drugs and the in vivo bioavailability of the drugs are highly influenced before reaching the targeted area sufficiently, due to physiological and anatomical barriers of the eye, such as rapid nasolacrimal drainage. Poor intraocular penetration and frequent administration may also cause ocular cytotoxicity. A novel approach to overcome these drawbacks is the use of injectable hydrogels administered intravitreously for sustained drug delivery to the target site. These injectable hydrogels are used as nanocarriers to intimately interact with specific diseased ocular tissues to increase the therapeutic efficacy and drug bioavailability of the anti-glaucomic drugs. The human eye is very delicate, and is sensitive to contact with any foreign body material. However, natural biopolymers are non-reactive, biocompatible, biodegradable, and lack immunogenic and inflammatory responses to the host whenever they are incorporated in drug delivery systems. These favorable biomaterial properties have made them widely applicable in biomedical applications, with minimal adversity. This review highlights the importance of using natural biopolymer-based intravitreal hydrogel drug delivery systems for glaucoma treatment over conventional methods.

This study examines the hemocompatibility of gellan-gum-based hybrid hydrogels, with varying gellan-gum concentrations and constant sodium alginate and silk fibroin concentrations, respectively, in accordance with ISO 10993-4 standards. While previous studies have focused on cytocompatibility, the hemocompatibility of these hydrogels remains underexplored. Hydrogels were formulated with 0.3%, 0.5%, 0.75%, and 1% gellan gum combined with 3% silk fibroin and 4.2% sodium alginate separately, using physical and ionic cross-linking. Swelling behavior was analyzed in phosphate (pH 7.4) and acetic (pH 1.2) buffers and surface morphology was examined by scanning electron microscopy (SEM). Hemocompatibility tests included complete blood count (CBC), coagulation assays, hemolysis index, erythrocyte morphology, and platelet adhesion analysis. Results showed that gellan gum–sodium alginate hydrogels exhibited faster swelling than gellan gum–silk fibroin formulations. SEM indicated smoother surfaces with sodium alginate, while silk fibroin increased roughness, further amplified by higher gellan-gum concentrations. Hemocompatibility assays confirmed normal profiles in formulations with 0.3%, 0.5%, and 0.75% gellan gum, while 1% gellan gum caused significant hemolytic and thrombogenic activity. These findings highlight the excellent hemocompatibility of gellan-gum-based hydrogels, especially the sodium alginate variants, supporting their potential in bioengineering, tissue engineering, and blood-contacting biomedical applications.

Age-related macular degeneration (AMD) is a progressive ocular disease marked by the deterioration of retinal photoreceptor cells, leading to central vision decline, predominantly affecting the elderly population worldwide. Current treatment modalities, such as anti-VEGF agents, laser therapy, and photodynamic therapy, aim to manage the condition, with emerging strategies like stem cell replacement therapy showing promise. However, challenges like immune rejection and cell survival hinder the efficacy of stem cell interventions. Regenerative medicine faces obstacles in maximizing stem cell potential due to limitations in mimicking the dynamic cues of the extracellular matrix (ECM) crucial for guiding stem cell behaviour. Innovative biomaterials like gellan gum hydrogels offer tailored microenvironments conducive to enhancing stem cell culture efficacy and tissue regeneration. Gellan gum-based hydrogels, renowned for biocompatibility and customizable mechanical properties, provide crucial support for cell viability, differentiation, and controlled release of therapeutic factors, making them an ideal platform for culturing human embryonic stem cells (hESCs). These hydrogels mimic native tissue mechanics, promoting optimal hESC differentiation while minimizing immune responses and facilitating localized delivery. This review explores the potential of Gellan Gum-Based Hydrogels in regenerative AMD therapy, emphasizing their role in enhancing hESC regeneration and addressing current status, treatment limitations, and future directions.