Parthenope University of Naples
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Complications of tunneled central venous catheter placement: a narrative review of risks, prevention, and management strategies
No full textBackground: Tunneled cuffed catheter (TCC) remains a crucial vascular access option for patients undergoing hemodialysis, particularly in those who are not candidates for arteriovenous fistulas or grafts. However, placement carries immediate and delayed complications. Objective: This narrative review aims to provide a comprehensive overview of the complications encountered during and after the placement of a TCC for hemodialysis, highlighting current evidence, risk factors, prevention strategies, and management approaches. Methods: A critical selection of relevant literature was performed through PubMed and Scopus databases, focusing on articles published in the last two decades. Particular attention was given to studies reporting on mechanical, infectious, thrombotic, and late-onset complications, as well as technical factors influencing outcomes. Results: Complications of TCCs can be classified as immediate (e.g., arterial puncture, pneumothorax, bleeding), early (e.g., catheter malposition, exit-site infections), and late (e.g., central venous stenosis, catheter-related bloodstream infections, thrombosis). Patient- and procedure-related factors increase risk. Ultrasound and fluoroscopy, strict sterility, and timely management reduce complications rates. Conclusion: TCCs are indispensable in selected patients, but understanding their complications is key to patient safety and outcomes. Optimal outcomes depend on accurate patient selection, operator expertise, and standardized post-placement care
Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network
No full textBackground and Objective: In recent years, DNA methylation-tumor classification based on artificial intelligence algorithms has led to a notable improvement in diagnostic accuracy compared to traditional machine learning methods. In cancer, the methylation pattern likely reflects both the cell of origin and somatically acquired DNA methylation changes, making this epigenetic modification an ideal tool for tumor classification. We propose an in-depth method based on the Convolutional Neural Network for the DNA methylation-based classification of papillary thyroid carcinoma (PTC) and its follicular (fvPTC) and classical (cvPTC) subtypes. Methods: To address this issue, we first performed a pan-cancer analysis to train a convolutional 1-D Neural Network (CNN) using supervised learning. Then, we evaluated the robustness of the net on an independent PTC dataset and assessed its ability to classify normal (N=56) versus tumor (N=461) samples and fvPTC (N=102) versus cvPTC (N=359). We then compared its performance with 4 machine learning models (logistic regression with elastic net penalty, quadratic discriminant analysis, support vector classifier with RBF kernel, and random forest). Results: By using RELU activation function and leaving out liquid tumors, our results show a remarkable performance of the neural network in classifying cancer and normal samples when applied to pan-cancer data (Validation AUC = 0.9903 and Validation Loss = 0.112). When applied to the thyroid independent dataset, the proposed Neural Net architecture successfully discriminates tumor versus normal samples (AUC = 0.91 +/- 0.05) and follicular versus classical PTC subtypes (AUC = 0.80 +/- 0.05), outperforming traditional machine learning algorithms. Conclusions: In conclusion, the study highlights the effectiveness of CNNs in the methylation based classification of thyroid tumors and their subtypes, demonstrating its ability to capture subtle epigenetic differences with minimal preprocessing. This versatility makes the model adaptable for classifying other tumor types. Also, the findings emphasize the potential relevance of AI algorithms in addressing complex diagnostic challenges and supporting clinical decisions. This research lays the foundation for developing robust and generalizable models that can advance precision oncology in cancer diagnostics
Engineering evaluation of grain-oriented steel solutions for special applications in High Energy Physics
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Unlocking the potential of nanocellulose in biomedical innovations: A sustainable marvel
No full textWith rapid urbanization and growing apprehensions due to environmental and ecological issues, the synthesis of novel functional and innovative materials is on the rise. If developed from natural resources, such complex chemicals and novel materials will be better for the environment. Such chemical products of great public value will encourage green synthesis. Cellulose and nanocellulose (NC) gained extensive consideration as a nano-reinforcement for polymer matrices, finding applications in countless businesses. Because of its intrinsic sustainability characteristics and abundant availability, NC stands out as a highly significant and promising ecological material in today's world. This review explores NC properties (such as Modification of hydroxyl groups, Covalent modification, and Functionalization with ionic groups), drawing on research where SEM, AFM, and XRD techniques analyze its morphology, surface properties, and crystallinity, significant variations, and a scientometric study. This review also summarizes recent advances and emerging uses of NC and its nanocomposites in biological and medical applications like wound dressing, tissue engineering and repair, stem cell therapy, smart drug delivery, biosensing, and new biomedical applications. NC has outstanding mechanical strength, Young's modulus, and biocompatibility, and is used to synthesize an extensive variety of nanomaterials, comprising metal, metal oxide, polymer, and carbon nanostructures and nanocomposites. It is also used in food packaging, reinforced polymer composites with high mechanical strength, tissue scaffolds, drug delivery, biosensors, filtration, biophotonics, and 3D bioprinting. The versatility of NC and its contribution to sustainable innovation establish it as a crucial material for environmental and medical advancements
Parliamentary Organisation, History and Knowledge
No full textThis study elucidates how the historical and organisational evolution of parliamentary staff is related to the establishment and development of organisational knowledge resources within parliamentary institutions. The use of parliamentary staff reflects an effort to acquire institutional expertise, knowledge and professionalism in the legislative branch to counterbalance a perceived advantage within executive agencies. Parliamentary staff contribute to constructing organisational memory and knowledge, by shaping and sharing knowledge resources that support legislative processes. Parliamentary staff preserve continuity, institutional memory, and expertise. The rise of expertise and knowledge within parliamentary staff is related to the increasing organisational complexity over time of parliamentary administrations that enables parliamentary staff to develop knowledge capabilities assets that contribute to fostering the effectiveness and decision-making capacity of parliamentary bodies. The organisational and professional development of parliamentary staff helps improve knowledge capabilities and expertise, supporting parliaments in exerting influence on policy making
Writing Research Articles for Climate Change Impacts on Coffee Areas: A Metadiscourse Analytical Survey
No full textBio-tracking, bio-monitoring and bio-magnification interdisciplinary studies to assess cyanobacterial harmful algal blooms (cyanoHABs)’ impact in complex coastal systems
No full text: Cyanobacterial Harmful Algal Blooms (cyanoHABs) represent significant threats to human health and environmental sustainability. These blooms, characterized by the rapid proliferation of toxic species, can release harmful toxins into aquatic environments, with severe consequences for ecosystems and human populations. Traditional research on cyanoHABs faces several limitations, including the lack of standardized detection methods, environmental variability, and low awareness of the associated risks. Most studies rely on conventional laboratory techniques, which are often resource-intensive and not widely accessible. Additionally, the complex dynamics of cyanoHABs, influenced by factors such as temperature, nutrients, and bloom evolution, make it difficult to establish consistent regulatory and monitoring frameworks. This paper presents a new integrated strategy that combines advanced technologies (remote sensing, in-situ multispectral analysis, mass spectrometry) with bio-monitoring and bio-tracking. This interdisciplinary approach improves the monitoring of cyanoHAB spread, tracks bioaccumulation in the food chain, and provides timely warnings for public health protection. The case study focuses on the Campi Flegrei area, an active volcanic region in Southern Italy, where Lake Avernus, a volcanic lake, has experienced periodic cyanobacterial blooms. This region also hosts mussel aquaculture and recreational activities. Remote sensing allowed the tracking of the 2022 bloom from the lake to the sea, reaching a mussel farm along the coast. Rapid detection and quantification of anabaenopeptins in bivalves enabled timely alerts to local authorities, prompting an assessment of contamination risks. The study demonstrates how the integration of remote sensing and molecular analysis enhances environmental monitoring by providing real-time, high-resolution data. This approach supports a better understanding of bloom dynamics, bioaccumulation, and impacts on the food chain, informing risk management and regulatory strategies. The research highlights the value of combining advanced technologies to improve the management of cyanoHAB-related risks, protecting both human health and ecosystem sustainability