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Infection01:20

Infection

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When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
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Urinary Tract Infection II: Pathophysiology01:25

Urinary Tract Infection II: Pathophysiology

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The pathophysiology of urinary tract infections (UTIs) encompasses several progressive stages, beginning with bacterial colonization and culminating in potential systemic complications if untreated. UTIs are primarily initiated by bacteria, such as Escherichia coli, which often originate from the gastrointestinal tract and migrate to the urinary system through the periurethral area. This migration can occur via several routes, including improper hygiene practices, sexual activity, or...
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Cystic Fibrosis: Pathogenesis01:23

Cystic Fibrosis: Pathogenesis

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Cystic fibrosis (CF), an autosomal recessive disorder, significantly affects the function of exocrine glands. This genetically inherited disease is characterized by the production of thick and sticky mucus, which can severely affect various organs and systems in the body.
CF is primarily caused by a genetic mutation in a chromosome 7 gene coding for the cystic fibrosis transmembrane conductance regulator (CFTR) protein. The most common gene mutation leading to CF is the ΔF508 mutation,...
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Pneumonia II: Pathophysiology01:29

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The pathophysiology of pneumonia involves the following steps:
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Stages of Infection01:26

Stages of Infection

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Stages of infection describe what happens to a susceptible host once a pathogen invades the human body. The stages of infection are incubation, prodromal, illness, stage of decline, and convalescence. The incubation stage is the period from exposure to a pathogen until symptoms start. The infected person is unaware of impending illness as the pathogens grow and multiply within the body. The duration may vary depending on the type of infection. The incubation period of measles averages ten to...
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Defense Against Bacterial Pathogens01:31

Defense Against Bacterial Pathogens

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The human immune system is a complex network of cells, tissues, and organs that work together to defend the body against bacterial infections. It consists of various immune cells, each playing a specific role in the defense mechanism.
Phagocytes
Phagocytes are the frontline soldiers of the immune system. They include neutrophils and macrophages. Neutrophils are the most abundant type of white blood cell and are quickly mobilized to the site of infection. Macrophages are larger cells that patrol...
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Related Experiment Video

Updated: Jan 8, 2026

Mouse Footpad Inoculation Model to Study Viral-Induced Neuroinflammatory Responses
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Basic Science and Pathogenesis.

Yacoub Abelard Njipouombe Nsangou1, Maria A Wörheide1, Jürgen Dönitz1,2

  • 1Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

This study integrates multi-omics data for Alzheimer's disease (AD) subtyping. The approach identifies distinct molecular subtypes, paving the way for personalized medicine in AD patients.

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Area of Science:

  • Neuroscience
  • Genomics
  • Biotechnology

Background:

  • Alzheimer's disease (AD) presents complex, heterogeneous patient profiles, hindering diagnosis and personalized treatment development.
  • Omics technologies (transcriptomics, metabolomics, proteomics) provide comprehensive molecular data for understanding AD.
  • Integrating multi-omics data can reveal disease mechanisms and identify patient subgroups for personalized medicine.

Purpose of the Study:

  • To propose a multi-omics data integration and disease subtyping approach for Alzheimer's disease.
  • To leverage data-driven multi-scale network structures from the AD Atlas for enhanced analysis.
  • To enable personalized medicine by identifying distinct Alzheimer's disease subtypes.

Main Methods:

  • Extracted network module features from transcriptomics, proteomics, and metabolomics data using WGCNA and PCA.
  • Applied deep graph representation learning and unsupervised clustering to identify 25 multi-omics clusters.
  • Utilized an autoencoder model for integrated multi-omics expression profiling and disease subtyping.

Main Results:

  • The autoencoder effectively learned low-dimensional multi-omics representations.
  • Identified molecular subtypes of AD not apparent through traditional analyses.
  • Demonstrated sensitivity of the brain multi-ome to AD neuropathology, clinical status, and other variables.

Conclusions:

  • The multi-omics integration methodology offers a robust framework for AD patient stratification.
  • Integration of multi-omics data and the AD Atlas network identified patient groups with shared clinical parameters.
  • Advanced understanding of Alzheimer's disease molecular heterogeneity and subtype-specific manifestations.