Sci

Assisted Reproductive Technology Units (ARTUs) constitute a rapidly growing sector in healthcare, where service quality and patient safety are closely intertwined with ethical principles, technological precision, and managerial efficiency. This study aims to explore quality management practices and certification standards—such as ISO 9001, ISO 15189, and ISO 13485—within ARTUs, with the goal of developing a model that enhances patient-centered outcomes. The analysis focuses on the roles of leadership, staff training, and internal auditing mechanisms as key factors for the successful implementation of quality management systems (QMSs). Through a structured literature review and thematic synthesis, this study identifies challenges that ARTUs face in aligning with international standards and highlights strategies that strengthen patient trust, transparency, and continuous improvement. The proposed model connects measurable quality indicators with patient perceptions and experiences, providing a comprehensive framework for sustainable quality development. This article contributes to the academic discourse on healthcare quality governance and offers practical insights for policymakers and administrators seeking to improve patient experience and organizational resilience in reproductive medicine.

IoT-based blockchain technology has improved the healthcare system to ensure the privacy and security of healthcare data. A Blockchain Bridge (BB) is a tool that enables multiple blockchain networks to communicate with each other. The existing approach combining the classical and quantum blockchain models failed to secure the data transmission during cross-chain communication. Thus, this study proposes a new BB verification for secure healthcare data transfer. Additionally, a brain tumor analysis framework is developed based on segmentation and neural networks. After the patient’s registration on the blockchain network, Brain Magnetic Resonance Imaging (MRI) data is encrypted using Hash-Keyed Quantum Cryptography and verified using a Peer-to-Peer Exchange model. The Brain MRI is preprocessed for brain tumor detection using the Fuzzy HaMan C-Means (FHMCM) segmentation technique. The features are extracted from the segmented image and classified using the LeCun Kaiming-based Convolutional ModSwish Neural Network (LCK-CMSNN) classifier. Subsequently, the brain tumor diagnosis report is securely transferred to the patient via a smart contract. The proposed model verified BB with a Verification Time (VT) of 12,541 ms, secured the input with a Security level (SL) of 98.23%, and classified the brain tumor with 99.15% accuracy, thus showing better performance than the existing models.

The winemaking industry represents one of the most important sectors of the Mediterranean agrifood economy, generating large amounts of solid residues, especially grape pomace. The study aimed to evaluate during two consecutive harvest years the influence of the production system (conventional vs. organic) and cultivar on the mineral, chemical, and antioxidant composition, as well as the colorimetric properties, of grape pomaces obtained from four Vitis vinifera L. cultivars in Alentejo-Portugal. The results showed that mineral composition was significantly affected by both production system and cultivar, with organic grape pomace showing higher K and Mn contents, whereas Ca and Cu showed consistently higher content under conventional. Protein content tended to increase under organic production, while fiber and fat were overall higher in conventional, particularly in the first year. Sugars displayed strong cultivar specificity, with Arinto showing the highest concentrations (30 to 40%), and considering all cultivars, total phenolic content ranged between 4000 ando 9000 mg GAE/100 g, while antioxidant capacity varied among cultivars and years. Colorimetric parameters were essentially influenced by cultivar and harvest year rather than production system. The PCA revealed that PC1 (44.06%) represented a gradient associated with mineral and antioxidant composition, while PC2 (21.26%) reflected minor variation in color and sugars, and the hierarchical clustering distinguished Syrah and Alicante Bouschet as the cultivars most responsive to production system, whereas Aragonez and Arinto exhibited greater compositional stability across years. Overall, the findings indicate that both cultivar and management practices (organic and conventional) influence the compositional profile of grape pomace, with organic showing a tendency to enhance K, Mn, protein, and antioxidant parameters, whereas conventional practices favored higher levels of Ca, Cu, and fiber. The results provide valuable insights for the valorization of grape pomace and the development of sustainable viticultural strategies in Mediterranean environments.