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Related Concept Videos

Alzheimer's Disease: Overview01:26

Alzheimer's Disease: Overview

Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ and tau...
Alzheimer's Disease: Treatment01:22

Alzheimer's Disease: Treatment

Alzheimer's Disease (AD), a neurodegenerative disorder, is pathologically identified by amyloid plaques and neurofibrillary tangles composed of tau protein. AD pharmacotherapy aims to manage cognitive symptoms, delay disease progression, and treat behavioral symptoms. The treatment is primarily symptomatic and palliative, with no definitive disease-modifying therapy available. Cholinesterase inhibitors, including donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne), are...
Dementia01:30

Dementia

Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
The progression of dementia is generally gradual.
Alzheimer Disease l: Introduction01:29

Alzheimer Disease l: Introduction

Alzheimer disease is a chronic, progressive, and irreversible neurodegenerative disorder and the most common cause of dementia in older adults. It leads to gradual neuronal loss, causing cognitive decline, behavioral changes, and loss of functional independence.Risk Factors and EtiologyThe disease is multifactorial. Age is the strongest risk factor, with prevalence doubling every 5 years after age 65. Genetic factors include mutations in genes such as APP, PSEN1, and PSEN2, which are associated...
Alzheimer Disease ll: Pathophysiology01:23

Alzheimer Disease ll: Pathophysiology

Alzheimer disease involves structural changes in the brain that begin long before symptoms appear. The most distinctive features are extracellular neuritic plaques and intracellular neurofibrillary tangles.Neuritic plaques form in the cerebral cortex and around blood vessels. These plaques contain a dense core of beta-amyloid (Aβ)—a toxic protein fragment that clumps outside neurons. The core is surrounded by damaged neuronal extensions, as well as reactive astrocytes and microglia. Abnormal...
Dementia l: Introduction01:22

Dementia l: Introduction

Dementia is an acquired, progressive syndrome characterized by a decline in multiple cognitive domains severe enough to impair daily functioning and reduce independence. Although memory loss is a central feature, the diagnosis requires additional deficits involving language, executive function, visuospatial skills, judgment, calculation, or abstract reasoning. These cognitive impairments reflect underlying neurodegenerative or vascular processes that gradually disrupt neuronal networks...

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Related Experiment Video

Updated: Jun 19, 2026

Examining the Characteristics of Episodic Memory using Event-related Potentials in Patients with Alzheimer's Disease
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Examining the Characteristics of Episodic Memory using Event-related Potentials in Patients with Alzheimer's Disease

Published on: August 30, 2011

Decoding Alzheimer's Disease One Cell Class at a Time.

Martin Darvas1, David G Cook2,3, Annalisa Scimemi4

  • 1Department of Laboratory Medicine and Pathology, School of Medicine, University of Washington, Seattle, WA, 98104, USA.

Cellular and Molecular Neurobiology
|February 10, 2026
PubMed
Summary
This summary is machine-generated.

Single-cell genomics and spatial transcriptomics reveal brain cell diversity. Integrating this data with other frameworks is crucial for understanding brain function and diseases like Alzheimer's disease.

Keywords:
Alzheimer’s diseaseAstrocytesAtlasExcitatory neuronsInterneuronsMicrogliaOligodendrocytesPrincipal cellsRNA-seq

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DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
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Quantitative Analysis of Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Stabilization in a Neural Model of Alzheimer's Disease (AD)
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Quantitative Analysis of Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Stabilization in a Neural Model of Alzheimer's Disease (AD)

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Last Updated: Jun 19, 2026

Examining the Characteristics of Episodic Memory using Event-related Potentials in Patients with Alzheimer's Disease
11:01

Examining the Characteristics of Episodic Memory using Event-related Potentials in Patients with Alzheimer's Disease

Published on: August 30, 2011

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
09:47

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

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Quantitative Analysis of Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Stabilization in a Neural Model of Alzheimer's Disease (AD)
06:41

Quantitative Analysis of Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Stabilization in a Neural Model of Alzheimer's Disease (AD)

Published on: January 10, 2025

Area of Science:

  • Neuroscience
  • Genomics
  • Cell Biology

Background:

  • Single-cell genomics and spatial transcriptomics are advancing brain cell classification.
  • Understanding cell clusters requires integrating transcriptomic data with anatomical, physiological, and functional information.
  • Cellular composition varies across brain regions, changes over time, and is altered in disease states like Alzheimer's disease.

Purpose of the Study:

  • To review current findings on multimodal imaging in neuroscience.
  • To discuss the integration of transcriptomic, structural, and functional data for brain research.
  • To highlight how integrative approaches are challenging existing knowledge of Alzheimer's disease.

Main Methods:

  • Review of multimodal imaging techniques, including single-cell genomics and spatial transcriptomics.
  • Analysis of studies integrating gene expression data with anatomical, physiological, and electrical properties.
  • Synthesis of research on cell cluster variations across brain regions and disease states.

Main Results:

  • Multimodal imaging provides new insights into the taxonomy of genetically defined mammalian brain cell clusters.
  • Integration of diverse data types is essential for interpreting transcriptomic findings.
  • Cellular composition and its relation to disease progression, such as in Alzheimer's disease, are complex and dynamic.

Conclusions:

  • Integrative approaches combining transcriptomic, structural, and functional data are vital for advancing neuroscience.
  • This integrated knowledge base is reshaping our understanding of the genetic, molecular, and cellular basis of Alzheimer's disease.
  • Future research should focus on comprehensive data integration to fully elucidate brain complexity and disease mechanisms.