About this Research Topic
This Research Topic is part of the series Translational Advances in Alzheimer's, Parkinson's, and other Neurodegenerative Dementias: Volume 1
Alzheimer’s disease (AD) is the most common devastating dementia and neurodegenerative disease in the elderly. The importance of diagnosing AD in its early stage is paramount to the aging population as the pathology is irreversible. Mild cognitive impairment (MCI) and subjective cognitive decline (SCD) are considered the primary clinical manifestations of AD and other dementia. However, precise detection of SCD, MCI, AD, and other dementia in an early phase is still challenging in daily clinical practice.
Moreover, changes in molecular characterizations, such as glucose metabolism, common or distinctive biomarkers such as Amyloid-Beta, and Tau protein are associated with the pathology of AD, whereas Alpha-Synuclein is proven to be related to Parkinson’s disease (PD) and other dementia.
For instance, it is possible to apply molecular imaging techniques, such as fluorodeoxyglucose (FDG), AV45, and AV1451 to detect the early phase of SCD, MCI, AD, PD, and other dementia. These techniques may also help to predict the time frame of disease progression from SCD or MCI into dementia.
Similarly, cerebrovascular diseases such as hemorrhagic stroke, ischemic stroke, and Moyamoya disease often result in vascular dementia (VaD). The early phase of VaD is reversible by appropriate manner timely treatment to improve regional blood flow and neural metabolism. Thus, early detection of vascular cognitive impairment is of clinical significance.
On the other hand, a variety of conditions may present with symptoms of dementia. These may include traumatic brain injury (TBI), brain tumors, and simple hydrocephalus. Sometimes, even simple aging process leads to senile dementia.
Bioinformatics research has developed thanks to the recent advancements in Artificial Intelligence (AI), which has become a powerful tool for different applications for example in the generation of diagnosis, progression and severity scores as measurable features allowing a further understanding describing the clinical situation.
As an interdisciplinary field of science and technology, it aims to develop methods, tools, and software to improve our understanding of biological data. Nowadays, researchers are facing difficulties in choosing the best method that could be reflected in a specific dataset in a comprehensible fashion, annotated with context, estimates of accuracy, and explanation.
This Research Topic aims to bring a multidisciplinary perspective and updated insight into the most recent advances in dementia. Reviews and original articles are welcome.
We welcome subtopics addressing, but not limited to:
- Application of bioinformatics and computational biology in big data mining that analyzes a specific database or medical records system to investigate AD, PD, and other dementia
- Clinical application of novel molecular imaging techniques for AD, PD, and other dementia detection in its early stage
- Innovative experimental research of emerging interest in AD, PD, and other dementia involving novel distinctive biomarkers using cellular, molecular approaches, and animal models
- Novel molecular imaging analysis methods based on AI to detect and predict the progression from SCD or MCI into AD, PD, and other dementia
Note for the authors: for all the manuscripts submitted via Pharmacology-Neuropharmacology; please submit only manuscripts that are within the scope of the section and have a relevant pharmacology focus.
Keywords: Alzheimer's disease, Parkinson's disease, Dementia, neurodegenerative disorders, big data mining, imaging methods, bioinformatic applications
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