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Author Cáeres, C.; Heusser, B.; Garnham, A.; Moczko, E.
Title The Major Hypotheses of Alzheimer's Disease: Related Nanotechnology-Based Approaches for Its Diagnosis and Treatment Type
Year 2023 Publication Cells Abbreviated Journal Cells
Volume 12 Issue 23 Pages 2669
Keywords neurodegeneration; neuroscience; Alzheimer's disease; nanotechnology; biomarkers; drug delivery; nanoparticles
Abstract Alzheimer's disease (AD) is a well-known chronic neurodegenerative disorder that leads to the progressive death of brain cells, resulting in memory loss and the loss of other critical body functions. In March 2019, one of the major pharmaceutical companies and its partners announced that currently, there is no drug to cure AD, and all clinical trials of the new ones have been cancelled, leaving many people without hope. However, despite the clear message and startling reality, the research continued. Finally, in the last two years, the Food and Drug Administration (FDA) approved the first-ever medications to treat Alzheimer's, aducanumab and lecanemab. Despite researchers' support of this decision, there are serious concerns about their effectiveness and safety. The validation of aducanumab by the Centers for Medicare and Medicaid Services is still pending, and lecanemab was authorized without considering data from the phase III trials. Furthermore, numerous reports suggest that patients have died when undergoing extended treatment. While there is evidence that aducanumab and lecanemab may provide some relief to those suffering from AD, their impact remains a topic of ongoing research and debate within the medical community. The fact is that even though there are considerable efforts regarding pharmacological treatment, no definitive cure for AD has been found yet. Nevertheless, it is strongly believed that modern nanotechnology holds promising solutions and effective clinical strategies for the development of diagnostic tools and treatments for AD. This review summarizes the major hallmarks of AD, its etiological mechanisms, and challenges. It explores existing diagnostic and therapeutic methods and the potential of nanotechnology-based approaches for recognizing and monitoring patients at risk of irreversible neuronal degeneration. Overall, it provides a broad overview for those interested in the evolving areas of clinical neuroscience, AD, and related nanotechnology. With further research and development, nanotechnology-based approaches may offer new solutions and hope for millions of people affected by this devastating disease.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2073-4409 ISBN Medium
Area Expedition Conference
Notes WOS:001115982700001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1916
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Author Goles, E.; Palacios, A.G.
Title Dynamical complexity in cognitive neural networks Type
Year 2007 Publication Biological Research Abbreviated Journal Biol. Res.
Volume 40 Issue 4 Pages 479-485
Keywords artificial; neural net; brain; dynamical complexity; computational Neurosciences; cellular automata
Abstract In the last twenty years an important effort in brain sciences, especially in cognitive science, has been the development of mathematical tool that can deal with the complexity of extensive recordings corresponding to the neuronal activity obtained from hundreds of neurons. We discuss here along with some historical issues, advantages and limitations of Artificial Neural Networks (ANN) that can help to understand how simple brain circuits work and whether ANN can be helpful to understand brain neural complexity.
Address [Goles, Eric] Univ Adolfo Ibanez, Fac Ciencias, Santiago, Chile, Email: eric.chacc@uai.cl
Corporate Author Thesis
Publisher Soc Biolgia Chile Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0716-9760 ISBN Medium
Area Expedition Conference
Notes WOS:000256072000009 Approved
Call Number UAI @ eduardo.moreno @ Serial 33
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