Current Alzheimer Research - Current Issue
Volume 22, Issue 9, 2025
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Neuroprotective Agents: Implications for Parkinson's Disease Treatment
More LessParkinson's disease (PD) is a multifaceted neurodegenerative condition marked by the progressive loss of dopaminergic neurons, leading to impairments in movement and cognition. This study offers an in-depth examination of the pathophysiological pathways associated with PD, emphasising the roles of oxidative stress, mitochondrial dysfunction, and neuroinflammation. The study examines the interaction between genetic and environmental factors in the development of PD, highlighting the significance of oxidative stress, mitochondrial dysfunction, and excitotoxicity in the degeneration of dopaminergic neurons. It also looks into the impact of neuroinflammation and microglial activation on the causes of PD. Despite considerable progress in research, there remains a lack of effective treatments that can modify the course of the disease, highlighting the pressing need for new therapeutic approaches that address mitochondrial malfunction, oxidative stress, and neuroinflammation. This study assesses the neuroprotective efficacy of various substances, notably natural agents like resveratrol, curcumin, ginsenoside, and melatonin, for managing PD. Although these natural chemicals show promise, further robust clinical trials are needed to confirm their effectiveness and safety, as well as to investigate their potential incorporation into conventional PD treatment.
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Therapeutic Advances in Alzheimer’s Disease: Integrating Natural, Semi-Synthetic, and Synthetic Drug Strategies
More LessAuthors: Brijesh Singh Chauhan, Yash Pal Singh, Burkhard Poeggeler and Sandeep Kumar SinghAlzheimer’s disease (AD) is a neurodegenerative disorder associated with age, marked by progressive memory loss linked to the decline of cholinergic neurons, accumulation of amyloid plaques, and the presence of Neurofibrillary Tangles (NFTs). Neuropil threads in the brain contribute to amyloidosis and dementia. Despite extensive research, AD’s etiology remains unclear, and currently, no promising therapy exists. This review examines the role of natural, semi-synthetic, and synthetic drugs in AD treatment. Natural drugs demonstrate safety and efficacy with minimal adverse effects, while most agents, whether natural or synthetic, target multiple steps or directly counteract amyloidogenesis, tau protein pathology, oxidative stress, NMDA receptor activity, inflammation, acetylcholine (AChE) function, or α, β, γ secretase activity. In pursuit of improved treatment outcomes, we explore the effectiveness and challenges of various therapeutic interventions. Our hypothesis underscores the importance of an integrated approach combining these drug types for tailored symptom relief, suggesting combined therapies may offer greater therapeutic benefits compared to single-drug approaches. The drugs discussed show potential in regulating AD, thereby presenting viable options for its management. However, to obtain more favorable results, additional studies are needed by combining these drugs.
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Mapping the Connection Between Circadian Rhythms, Metabolism, and Neurodegeneration: Exploring Therapeutic Strategies
More LessAuthors: Rakesh Bhaskar, Kannan Badri Narayanan, Krishna Kumar Singh and Sung Soo HanCircadian rhythms are crucial for essential physiological functions such as metabolism, sleep-wake cycles, hormone balance, and cognitive abilities, which are regulated by the central Suprachiasmatic Nucleus (SCN) and peripheral clocks. Disruptions to circadian rhythms, which may be caused by aging, lifestyle factors, and environmental influences, are linked to metabolic disorders and Neurodegenerative Diseases (NDs). This review examines the reciprocal relationship between circadian control and metabolism, highlighting the molecular processes that maintain circadian rhythms and how these processes change with age. Aging diminishes SCN efficiency and disrupts peripheral clock alignment, leading to impaired physiological functions, increased oxidative stress, and neuroinflammation, all of which contribute to the progression of NDs such as Alzheimer’s (AD), Parkinson's disease (PD), Huntington's disease (HD), etc. Emerging therapeutic strategies aim to restore circadian function through interventions, including bright light therapy, melatonin supplementation, and pharmacological agents targeting clock gene regulators and neuropeptides. Furthermore, lifestyle modifications, such as Structured Physical Activity (SPA) and Time-Restricted Feeding (TRF), can enhance circadian health by synchronizing metabolic and hormonal rhythms. Future directions include chrono-pharmacology, gene editing, and Artificial Intelligence (AI)-driven personalized medicine, all of which emphasize the development of tailored circadian therapies. Advancing circadian research holds the potential to facilitate better health outcomes and improve quality of life, while also addressing the growing concerns of the aging population and NDs.
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RESIGN: Alzheimer's Disease Detection Using Hybrid Deep Learning based Res-Inception Seg Network
More LessAuthors: Amsavalli Kannan, Kanaga Suba Raja Subramanian and Sudha SureshIntroductionAlzheimer's disease (AD) is a leading cause of death, making early detection critical to improve survival rates. Conventional manual techniques struggle with early diagnosis due to the brain's complex structure, necessitating the use of dependable deep learning (DL) methods. This research proposes a novel RESIGN model is a combination of Res-InceptionSeg for detecting AD utilizing MRI images.
MethodsThe input MRI images were pre-processed using a Non-Local Means (NLM) filter to reduce noise artifacts. A ResNet-LSTM model was used for feature extraction, targeting White Matter (WM), Grey Matter (GM), and Cerebrospinal Fluid (CSF). The extracted features were concatenated and classified into Normal, MCI, and AD categories using an Inception V3-based classifier. Additionally, SegNet was employed for abnormal brain region segmentation.
ResultsThe RESIGN model achieved an accuracy of 99.46%, specificity of 98.68%, precision of 95.63%, recall of 97.10%, and an F1 score of 95.42%. It outperformed ResNet, AlexNet, DenseNet, and LSTM by 7.87%, 5.65%, 3.92%, and 1.53%, respectively, and further improved accuracy by 25.69%, 5.29%, 2.03%, and 1.71% over ResNet18, CLSTM, VGG19, and CNN, respectively.
DiscussionThe integration of spatial-temporal feature extraction, hybrid classification, and deep segmentation makes RESIGN highly reliable in detecting AD. A 5-fold cross-validation proved its robustness, and its performance exceeded that of existing models on the ADNI dataset. However, there are potential limitations related to dataset bias and limited generalizability due to uniform imaging conditions.
ConclusionThe proposed RESIGN model demonstrates significant improvement in early AD detection through robust feature extraction and classification by offering a reliable tool for clinical diagnosis.
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Volumes & issues
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Volume 22 (2025)
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Volume 21 (2024)
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Volume 20 (2023)
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Volume 19 (2022)
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Volume 18 (2021)
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Volume 17 (2020)
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Volume 16 (2019)
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Volume 15 (2018)
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Volume 14 (2017)
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Volume 13 (2016)
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Volume 12 (2015)
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Volume 11 (2014)
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Volume 10 (2013)
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Volume 9 (2012)
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Volume 8 (2011)
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Volume 7 (2010)
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Volume 6 (2009)
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Volume 5 (2008)
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Volume 4 (2007)
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Volume 3 (2006)
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Volume 2 (2005)
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Volume 1 (2004)
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Cognitive Reserve in Aging
Authors: A. M. Tucker and Y. Stern
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