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Related Concept Videos

Ischemic Stroke l: Introduction01:15

Ischemic Stroke l: Introduction

Ischemic stroke is an acute cerebrovascular condition in which blood flow to a brain region is suddenly interrupted, leading to tissue infarction. Neurons depend on continuous oxygen and glucose supply, so even brief reductions in perfusion cause energy failure, ionic imbalance, and irreversible injury. Ischemic strokes are classified into thrombotic and embolic types based on their underlying mechanisms.Thrombotic MechanismsThrombotic stroke develops when a clot forms within a cerebral artery.
Ischemic Stroke ll: Pathophysiology01:15

Ischemic Stroke ll: Pathophysiology

An ischemic stroke occurs when a cerebral blood vessel becomes obstructed, most often by a thrombus or embolus, interrupting the delivery of oxygen and glucose to brain tissue. Because neurons rely on continuous aerobic metabolism, energy failure begins within minutes of reduced perfusion. The region receiving the least blood flow becomes the infarct core, an area of irreversible cellular death. Surrounding this core lies the penumbra, a zone of hypoperfused but still viable tissue that is...

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Related Experiment Video

Updated: May 11, 2026

Modeling Stroke in Mice - Middle Cerebral Artery Occlusion with the Filament Model
06:28

Modeling Stroke in Mice - Middle Cerebral Artery Occlusion with the Filament Model

Published on: January 6, 2011

91.9K

Inflammation-Derived and Clinical Indicator-Based Predictive Model for Ischemic Stroke Recovery.

Jiao Luo1,2, You Cai3,4, Peng Xiao1

  • 1Department of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.

Journal of the American Heart Association
|July 23, 2024
PubMed
Summary

A new model combining inflammation markers (tissue inhibitor metalloproteinase-1 and galectin-3) and clinical factors accurately predicts stroke recovery. This tool aids in evaluating prognosis and developing targeted treatments for ischemic stroke patients.

Keywords:
LGALS3TIMP1ischemic strokeneuroinflammationrecovery biomarkers

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Area of Science:

  • Biomarker discovery
  • Neuroscience
  • Translational medicine

Background:

  • Neuroinflammation significantly impacts stroke prognosis.
  • Accurate prediction of functional outcomes in subacute ischemic stroke is crucial.

Purpose of the Study:

  • To develop a predictive model for functional outcomes in subacute ischemic stroke.
  • To identify inflammation-derived markers and clinical indicators for prognostic assessment.

Main Methods:

  • Proteomics and RNA sequencing identified candidate biomarkers.
  • Machine learning models were trained and validated using clinical and biomarker data.
  • Inflammation markers tissue inhibitor metalloproteinase-1 (TIMP1) and galectin-3 (LGALS3) were assessed.

Main Results:

  • TIMP1 and LGALS3 levels were elevated in stroke patients compared to controls.
  • A combined model including TIMP1, LGALS3, hemoglobin, LDL cholesterol, and uric acid achieved an AUC of 0.8 for outcome prediction.
  • The model demonstrated high accuracy in distinguishing between little effective (LE) and obvious effective (OE) recovery groups.

Conclusions:

  • The developed model is a valuable tool for prognostic evaluation in ischemic stroke.
  • Identified predictive factors can guide the development of improved therapeutic strategies.
  • This approach enhances the understanding of neuroinflammation's role in stroke recovery.