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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

Pneumonia II: Pathophysiology

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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 7, 2026

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

Sifat R Wahid1, Arshia A Khan1

  • 1University of Minnesota Duluth, Duluth, MN, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 25, 2025
PubMed
Summary

Brain-Machine Interfaces (BMIs) offer a novel approach for early dementia detection and personalized rehabilitation by monitoring neural biomarkers. This technology shows promise in identifying cognitive decline and enhancing patient engagement for improved dementia care.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Cognitive Science

Background:

  • Dementia affects over 55 million globally, with limited success from traditional interventions.
  • Alzheimer's disease constitutes 60-70% of dementia cases.
  • Brain-Machine Interfaces (BMIs) offer a novel approach for early detection and rehabilitation.

Purpose of the Study:

  • Investigate the feasibility of non-invasive BMIs for monitoring cognitive health in dementia patients.
  • Explore BMIs for early dementia detection using neural biomarkers.
  • Assess BMIs for personalized dementia rehabilitation and patient engagement.

Main Methods:

  • Utilize non-invasive sensors (EEG, fNIRS) to monitor dementia-related neural biomarkers like theta-gamma oscillations and P300.

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  • Employ machine learning algorithms for early dementia risk classification.
  • Implement real-time neurofeedback and gamified interfaces for cognitive rehabilitation.
  • Main Results:

    • EEG and machine learning classifiers show promising results for dementia detection.
    • A BiLSTM model achieved 97.27% accuracy in detecting dementia from EEG signals.
    • Passive monitoring via wearable BMIs can detect anomalies during daily activities.

    Conclusions:

    • BMIs hold transformative potential for dementia care, integrating early detection with personalized rehabilitation.
    • BMIs can identify at-risk individuals years before symptom onset.
    • Adaptive neurofeedback systems may slow cognitive decline by strengthening cognitive reserve.