Potential mechanisms of non-coding RNA regulation in Alzheimer's disease.

Alzheimer's disease, a progressively degenerative neurological disorder, is the most common cause of dementia in the elderly. While its precise etiology remains unclear, researchers have identified diverse pathological characteristics and molecular pathways associated with its progression. Advances in scientific research have increasingly highlighted the crucial role of non-coding RNAs in the progression of Alzheimer's disease.

Molecular Mechanisms of GFAP and PTPRC in Alzheimer's Disease: An Analysis of Neuroinflammatory Response and Progression.

Introduction: Alzheimer's disease (AD) is a complex neurological disorder that progressively worsens. Although its exact causes are not fully understood, new research indicates that genes related to non-neuronal cells change significantly with age, playing key roles in AD's pathology.

Method: This study focuses on a protein network centered on Glial Fibrillary Acidic Protein (GFAP) and Protein Tyrosine Phosphatase Receptor Type C (PTPRC).

Using Entropy as the Convergence Criteria of Ant Colony Optimization and the Application at Gene Chip Data Analysis.

Introduction: When Ant Colony Optimization algorithm (ACO) is adept at identifying the shortest path, the temporary solution is uncertain during the iterative process. All temporary solutions form a solution set.

Methods: Where each solution is random.

The features analysis of hemoglobin expression on visual information transmission pathway in early stage of Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized primarily by cognitive impairment. The motivation of this paper is to explore the impact of the visual information transmission pathway (V-H pathway) on AD, and the following feature were observed: Hemoglobin expression on the V-H pathway becomes dysregulated as AD occurs so as to the pathway becomes dysfunctional. According to the feature, the following conclusion was proposed: As AD occurs, abnormal tau proteins penetrate bloodstream and arrive at the brain regions of the pathway.

Sensitivity of substrate translocation in chaperone-mediated autophagy to Alzheimer's disease progression.

Alzheimer's disease (AD) is a progressive brain disorder marked by abnormal protein accumulation and resulting proteotoxicity. This study examines Chaperone-Mediated Autophagy (CMA), particularly substrate translocation into lysosomes, in AD. The study observes: (1) Increased substrate translocation activity into lysosomes, vital for CMA, aligns with AD progression, highlighted by gene upregulation and more efficient substrate delivery.

The coherence between PSMC6 and α-ring in the 26S proteasome is associated with Alzheimer's disease.

Alzheimer's disease (AD) is a heterogeneous age-dependent neurodegenerative disorder. Its hallmarks involve abnormal proteostasis, which triggers proteotoxicity and induces neuronal dysfunction. The 26S proteasome is an ATP-dependent proteolytic nanomachine of the ubiquitin-proteasome system (UPS) and contributes to eliminating these abnormal proteins.

An Exploration of the Coherent Effects between METTL3 and NDUFA10 on Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized primarily by a decline in cognitive function. However, the etiopathogenesis of AD is unclear. N6-methyladenosine (m6A) is abundant in the brain, and it is interesting to explore the relationship between m6A and AD causes.

The relationship between protein modified folding molecular network and Alzheimer's disease pathogenesis based on BAG2-HSC70-STUB1-MAPT expression patterns analysis.

Background: Alzheimer's disease (AD) is the most common cause of dementia and cognitive decline, while its pathological mechanism remains unclear. Tauopathies is one of the most widely accepted hypotheses. In this study, the molecular network was established and the expression pattern of the core gene was analyzed, confirming that the dysfunction of protein folding and degradation is one of the critical factors for AD.

Corrigendum: Exploring the interaction between T-cell antigen receptor-related genes and MAPT or ACHE using integrated bioinformatics analysis.

[This corrects the article DOI: 10.3389/fneur.2023.

Exploring the interaction between T-cell antigen receptor-related genes and MAPT or ACHE using integrated bioinformatics analysis.

Alzheimer's disease (AD) is a neurodegenerative disease that primarily occurs in elderly individuals with cognitive impairment. Although extracellular β-amyloid (Aβ) accumulation and tau protein hyperphosphorylation are considered to be leading causes of AD, the molecular mechanism of AD remains unknown. Therefore, in this study, we aimed to explore potential biomarkers of AD.

Preliminary exploration of the co-regulation of Alzheimer's disease pathogenic genes by microRNAs and transcription factors.

Background: Alzheimer's disease (AD) is the most common form of age-related neurodegenerative disease. Unfortunately, due to the complexity of pathological types and clinical heterogeneity of AD, there is a lack of satisfactory treatment for AD. Previous studies have shown that microRNAs and transcription factors can modulate genes associated with AD, but the underlying pathophysiology remains unclear.

Bioinformatics-based study reveals that AP2M1 is regulated by the circRNA-miRNA-mRNA interaction network and affects Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurological disease that worsens with time. The hallmark illnesses include extracellular senile plaques caused by β-amyloid protein deposition, neurofibrillary tangles caused by tau protein hyperphosphorylation, and neuronal loss accompanying glial cell hyperplasia. Noncoding RNAs are substantially implicated in related pathophysiology, according to mounting data.

Identification and Analysis of Alzheimer's Candidate Genes by an Amplitude Deviation Algorithm.

Background: Alzheimer's disease (AD) is the most common form of senile dementia. However, its pathological mechanisms are not fully understood. In order to comprehend AD pathological mechanisms, researchers employed AD-related DNA microarray data and diverse computational algorithms.

Assessment of gene order computing methods for Alzheimer's disease.

Background: Computational genomics of Alzheimer disease (AD), the most common form of senile dementia, is a nascent field in AD research. The field includes AD gene clustering by computing gene order which generates higher quality gene clustering patterns than most other clustering methods. However, there are few available gene order computing methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO).

Gene order computation using Alzheimer's DNA microarray gene expression data and the Ant Colony Optimisation algorithm.

As Alzheimer's Disease (AD) is the most common form of dementia, the study of AD-related genes via biocomputation is an important research topic. One method of studying AD-related gene is to cluster similar genes together into a gene order. Gene order is a good clustering method as the results can be optimal globally while other clustering methods are only optimal locally.

A special local clustering algorithm for identifying the genes associated with Alzheimer's disease.

Clustering is the grouping of similar objects into a class. Local clustering feature refers to the phenomenon whereby one group of data is separated from another, and the data from these different groups are clustered locally. A compact class is defined as one cluster in which all similar elements cluster tightly within the cluster.