Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Self-Presentation01:25

Self-Presentation

318
Self-presentation is a fundamental aspect of social interaction, shaping both how others perceive individuals and how they view themselves. This dynamic process influences behaviors in various social settings, often leading people to adjust their appearance, speech, and demeanor to align with their desired identity. While self-presentation can be deliberate or unconscious, it plays a critical role in interpersonal relationships and self-perception.Forms of Self-PresentationSelf-presentation can...
318
Self-Presentation: Self-Monitoring and Self-Handicapping02:05

Self-Presentation: Self-Monitoring and Self-Handicapping

44.7K
People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about...
44.7K
Strategies of Self-Presentation I: Strategic Self-Presentation01:12

Strategies of Self-Presentation I: Strategic Self-Presentation

216
Strategic self-presentation refers to individuals' intentional efforts to influence how others perceive them. This process is employed in various social and professional settings, such as job interviews, dating, politics, and legal contexts, where individuals seek to shape impressions to gain social or material advantages. While people generally present themselves in ways that align with their authentic characteristics, external factors, such as cognitive load, can hinder their ability to...
216
Processes of Self-Presentation01:29

Processes of Self-Presentation

247
Effective self-presentation is a central component of social interaction and identity construction. It relies on the dynamic processes of defining the situation and engaging in self-disclosure. These mechanisms help individuals navigate social context expectations and manage how others perceive them, fostering mutual understanding and relationship development.Defining the SituationSocial situations are shaped by collectively understood frames—a set of widely understood rules or...
247
Protein Networks02:26

Protein Networks

4.5K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.5K
Understanding the Self01:28

Understanding the Self

283
The self is a central aspect of human identity, encompassing an individual’s beliefs, emotions, perceptions, and experiences. It is a cognitive and psychological construct that enables individuals to interpret their traits and behaviors, influencing how they perceive themselves and interact with the world. While personality consists of stable and enduring characteristics, the self is shaped by self-perception and social experiences. This distinction highlights the dynamic nature of the...
283

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Reactivation of Oxidized Soluble Guanylate Cyclase as a Novel Treatment Strategy to Slow Progression of Calcific Aortic Valve Stenosis: Preclinical and Randomized Clinical Trials to Assess Safety and Efficacy.

Circulation·2025
Same author

Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis.

JACC. Cardiovascular imaging·2024
Same author

A deep patient-similarity learning framework for the assessment of diastolic dysfunction in elderly patients.

European heart journal. Cardiovascular Imaging·2024
Same author

Prediction of coronary artery calcium scoring from surface electrocardiogram in atherosclerotic cardiovascular disease: a pilot study.

European heart journal. Digital health·2023
Same author

Diastolic Function Assessment in Atrial Fibrillation Conundrum.

International journal of heart failure·2022
Same author

Electrocardiogram-Based Machine Learning Emulator Model for Predicting Novel Echocardiography-Derived Phenogroups for Cardiac Risk-Stratification: A Prospective Multicenter Cohort Study.

Journal of patient-centered research and reviews·2022

Related Experiment Video

Updated: Jan 29, 2026

Author Spotlight: Development of a Minimally Invasive Large-Animal Model for Reliable and Reproducible Cardiovascular Research
06:51

Author Spotlight: Development of a Minimally Invasive Large-Animal Model for Reliable and Reproducible Cardiovascular Research

Published on: October 20, 2023

1.7K

Network Tomography for Understanding Phenotypic Presentations in Aortic Stenosis.

Grace Casaclang-Verzosa1, Sirish Shrestha1, Muhammad Jahanzeb Khalil1

  • 1Division of Cardiology, West Virginia University Heart & Vascular Institute, Morgantown, West Virginia.

JACC. Cardiovascular Imaging
|February 9, 2019
PubMed
Summary

This study used topological data analysis to create a patient similarity network for aortic stenosis (AS), revealing distinct patterns of left ventricular (LV) dysfunction. The findings were validated in a murine model, offering insights into AS progression and treatment response.

Keywords:
aortic stenosisleft ventricular functionpatient similaritytopological data analysis

More Related Videos

A Rabbit Aortic Valve Stenosis Model Induced by Direct Balloon Injury
07:10

A Rabbit Aortic Valve Stenosis Model Induced by Direct Balloon Injury

Published on: March 31, 2023

1.6K
Murine Model of Central Venous Stenosis using Aortocaval Fistula with an Outflow Stenosis
06:17

Murine Model of Central Venous Stenosis using Aortocaval Fistula with an Outflow Stenosis

Published on: July 11, 2019

7.9K

Related Experiment Videos

Last Updated: Jan 29, 2026

Author Spotlight: Development of a Minimally Invasive Large-Animal Model for Reliable and Reproducible Cardiovascular Research
06:51

Author Spotlight: Development of a Minimally Invasive Large-Animal Model for Reliable and Reproducible Cardiovascular Research

Published on: October 20, 2023

1.7K
A Rabbit Aortic Valve Stenosis Model Induced by Direct Balloon Injury
07:10

A Rabbit Aortic Valve Stenosis Model Induced by Direct Balloon Injury

Published on: March 31, 2023

1.6K
Murine Model of Central Venous Stenosis using Aortocaval Fistula with an Outflow Stenosis
06:17

Murine Model of Central Venous Stenosis using Aortocaval Fistula with an Outflow Stenosis

Published on: July 11, 2019

7.9K

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Data Science

Background:

  • Aortic stenosis (AS) presents with variable left ventricular (LV) responses and heterogeneous phenotypes.
  • Understanding these variations is crucial for effective patient management.

Purpose of the Study:

  • To construct a patient-patient similarity network for aortic stenosis (AS) using multi-feature left ventricular (LV) data.
  • To validate the network's topology and findings in an experimental murine model of AS.

Main Methods:

  • Utilized topological data analysis (TDA) on cross-sectional echocardiographic data from 246 AS patients.
  • Developed a patient similarity network representing multivariate AS features.
  • Compared network topology with data from 155 mice at various stages of AS.

Main Results:

  • The patient similarity network formed a loop, distinguishing mild and severe AS, linked by moderate AS.
  • Patients with reduced ejection fraction (EF) occupied one loop arm, while preserved EF patients occupied another.
  • Severe AS patients faced over 3 times higher risk for aortic valve replacement (AVR).
  • Post-AVR, patients showed recovery, moving towards milder AS zones.
  • TDA in mice mirrored human findings, showing similar progression patterns and frequent LV dysfunction.

Conclusions:

  • Machine learning-driven multifeature patient similarity assessments can precisely identify LV response patterns in AS progression.
  • This approach aids in understanding AS heterogeneity and guiding therapeutic strategies.