Strategies for Treatment of Disease-Associated Dementia Beyond Alzheimer's Disease: An Update

Effects of aerobic and resistance exercises on psychological and cognitive functions in patients with post-stroke migraine

OBJECTIVE

To investigate the impact of a combination of aerobic and resistance exercises on the psychological and cognitive functions of post-stroke migraine patients.

METHODS

This study recruited 100 patients suffering from post-stroke migraine pain who were admitted to the hospital, categorizing them into a control group (n = 50) and an intervention group (n = 50). The control group received conventional drug treatment, while the intervention group received the exercise-based intervention that combined aerobic exercise with resistance exercise.

RESULTS

Before treatment, both groups displayed similar Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Mini-mental State Examination (MMSE) and MoCA scores. However, after the intervention, the intervention group exhibited lower scores on these measures compared to the control group (all p < 0.05). Additionally, there were no discernible disparity in Migraine Disability Assessment (MIDAS) and Headache Impact Test (HIT-6) scores between the two cohorts of patients before treatment (p > 0.05), whereas the intervention group demonstrated significantly lower MIDAS and HIT-6 scores following the intervention (p < 0.05). Although there were no discernible distinctions in National Institute of Health stroke scale (NIHSS) and Stroke Specialized Quality of Life Scale (SS-QOL) measurements between the two patient groups before treatment (p > 0.05), the intervention group exhibited a significant decrease in NIHSS scores and a notable increase in SS-QOL scores after the intervention (p > 0.05). Moreover, the satisfaction rate and overall satisfaction rate were significantly higher in the intervention group (p < 0.05).

CONCLUSION

The combination of aerobic and resistance exercises demonstrated positive effects on the psychological well-being and overall quality of life for post-stroke migraine patients.

True or false? Alzheimer's disease is type 3 diabetes: Evidences from bench to bedside

Globally, Alzheimer's disease (AD) is the most widespread chronic neurodegenerative disorder, leading to cognitive impairment, such as aphasia and agnosia, as well as mental symptoms, like behavioral abnormalities, that place a heavy psychological and financial burden on the families of the afflicted. Unfortunately, no particular medications exist to treat AD, as the current treatments only impede its progression.The link between AD and type 2 diabetes (T2D) has been increasingly revealed by research; the danger of developing both AD and T2D rises exponentially with age, with T2D being especially prone to AD. This has propelled researchers to investigate the mechanism(s) underlying this connection. A critical review of the relationship between insulin resistance, Aβ, oxidative stress, mitochondrial hypothesis, abnormal phosphorylation of Tau protein, inflammatory response, high blood glucose levels, neurotransmitters and signaling pathways, vascular issues in AD and diabetes, and the similarities between the two diseases, is presented in this review. Grasping the essential mechanisms behind this detrimental interaction may offer chances to devise successful therapeutic strategies.

Virtual screening of acetylcholinesterase inhibitors through pharmacophore-based 3D-QSAR modeling, ADMET, molecular docking, and MD simulation studies

Alzheimer's disease (AD) is a leading cause of dementia in elderly patients. The pathophysiology of AD includes various pathways, such as the degradation of acetylcholine, amyloid-beta deposition, neurofibrillary tangle formation, and neuroinflammation. Many studies showed that targeting acetylcholinesterase enzyme (AChE) to improve acetylcholine can be an effective option to treat AD. In the current work, we employed a 3D QSAR-based approach to generate a pharmacophore to screen a chemical library of compounds that may inhibit AChE. Data from experimental studies were collected and used for the generation of pharmacophores. More than 1 million compounds were screened, and further drug-like properties were determined via in-silico ADMET studies. Techniques like molecular docking and molecular dynamics simulation were performed to analyze the binding of novel AChE inhibitors. A novel AChE inhibitor ligand-1 was identified as best with a docking score of -13.560 kcal/mol with RMSD of 1.71 Å during a 100 ns MD run. Further biological studies can give an insight into the potential of ligand-1 as a therapeutic agent for AD.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00189-1.

Machine learning in Alzheimer's disease drug discovery and target identification

Alzheimer's disease (AD) stands as a formidable neurodegenerative ailment that poses a substantial threat to the elderly population, with no known curative or disease-slowing drugs in existence. Among the vital and time-consuming stages in the drug discovery process, disease modeling and target identification hold particular significance. Disease modeling allows for a deeper comprehension of disease progression mechanisms and potential therapeutic avenues. On the other hand, target identification serves as the foundational step in drug development, exerting a profound influence on all subsequent phases and ultimately determining the success rate of drug development endeavors. Machine learning (ML) techniques have ushered in transformative breakthroughs in the realm of target discovery. Leveraging the strengths of large dataset analysis, multifaceted data processing, and the exploration of intricate biological mechanisms, ML has become instrumental in the quest for effective AD treatments. In this comprehensive review, we offer an account of how ML methodologies are being deployed in the pursuit of drug discovery for AD. Furthermore, we provide an overview of the utilization of ML in uncovering potential intervention strategies and prospective therapeutic targets for AD. Finally, we discuss the principal challenges and limitations currently faced by these approaches. We also explore the avenues for future research that hold promise in addressing these challenges.

Multi-Target-Directed Cinnamic Acid Hybrids Targeting Alzheimer's Disease

Progressive cognitive decline in Alzheimer's disease (AD) is a growing challenge. Present therapies are based on acetylcholinesterase inhibition providing only temporary relief. Promising alternatives include butyrylcholinesterase (BuChE) inhibitors, multi-target ligands (MTDLs) that address the multi-factorial nature of AD, and compounds that target oxidative stress and inflammation. Cinnamate derivatives, known for their neuroprotective properties, show potential when combined with established AD agents, demonstrating improved efficacy. They are being positioned as potential AD therapeutic leads due to their ability to inhibit Aβ accumulation and provide neuroprotection. This article highlights the remarkable potential of cinnamic acid as a basic structure that is easily adaptable and combinable to different active groups in the struggle against Alzheimer's disease. Compounds with a methoxy substitution at the para-position of cinnamic acid display increased efficacy, whereas electron-withdrawing groups are generally more effective. The effect of the molecular volume is worthy of further investigation.

Pathogenesis, Animal Models, and Drug Discovery of Alzheimer's Disease

Alzheimer's disease (AD), the most common cause of dementia, is a chronic neurodegenerative disease induced by multiple factors. The high incidence and the aging of the global population make it a growing global health concern with huge implications for individuals and society. The clinical manifestations are progressive cognitive dysfunction and lack of behavioral ability, which not only seriously affect the health and quality of life of the elderly, but also bring a heavy burden to the family and society. Unfortunately, almost all the drugs targeting the classical pathogenesis have not achieved satisfactory clinical effects in the past two decades. Therefore, the present review provides more novel ideas on the complex pathophysiological mechanisms of AD, including classical pathogenesis and a variety of possible pathogenesis that have been proposed in recent years. It will be helpful to find out the key target and the effect pathway of potential drugs and mechanisms for the prevention and treatment of AD. In addition, the common animal models in AD research are outlined and we examine their prospect for the future. Finally, Phase I, II, III, and IV randomized clinical trials or on the market of drugs for AD treatment were searched in online databases (Drug Bank Online 5.0, the U.S. National Library of Medicine, and Alzforum). Therefore, this review may also provide useful information in the research and development of new AD-based drugs.