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Related Concept Videos

Short-distance Transport of Resources02:12

Short-distance Transport of Resources

Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
Carrier-Mediated Transport01:06

Carrier-Mediated Transport

Carrier-mediated transport is a pivotal process in drug absorption, particularly for lipid-insoluble drugs, and encompasses facilitated diffusion and active transport. Facilitated diffusion allows drugs to move along their concentration gradient without energy expenditure, while active transport utilizes ATP to drive drug movement against this gradient.
Active transport involves two types of membrane-spanning transporters: uptake and efflux. Uptake transporters are expressed in the small...
Nonlinear Pharmacokinetics: Role of Transporters01:27

Nonlinear Pharmacokinetics: Role of Transporters

A drug's nonlinear kinetics can be influenced by a diverse range of transporter proteins that serve as crucial players in drug distribution. These transporters, found within cells, can enhance or reduce local drug concentrations by facilitating the influx or efflux of drugs. For instance, the expression of xenobiotic transporters can be influenced by factors such as age and gender, potentially impacting the linearity of drug response.
Polymorphisms occurring in drug transporters can alter...
Transport Across the Golgi01:26

Transport Across the Golgi

While it is unclear how molecules move between adjacent Golgi cisternae, it is apparent that the molecules move from cis- cisterna, the entry face, to the trans- cisterna, the exit face. Experiments initially suggested vesicles that bud from one cisterna and fuse with the next cisterna to transport proteins between the cisternae. This vesicular transport model describes the Golgi apparatus as a relatively static structure with a unique enzyme composition in each cisterna. Molecules are...
Reynolds Transport Theorem01:24

Reynolds Transport Theorem

The Reynolds transport theorem provides a framework to relate the time rate of change of an extensive property within a system to that in a control volume, which is crucial for analyzing fluid dynamics. Extensive properties, such as mass, velocity, acceleration, temperature, and momentum, can be expressed in terms of the mass of a fluid portion. These properties are called extensive because they depend on the system's size, while intensive properties are their corresponding values per unit mass.

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Updated: Jun 25, 2026

Characterizing the Composition of Molecular Motors on Moving Axonal Cargo Using "Cargo Mapping" Analysis
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CARGO: A Cytometry Analysis framework via Regularized Graph Optimal-transport.

Abida Sanjana Shemonti1, Grzegorz B Gmyrek2, Katrien L A Quintelier3,4,5

  • 1Department of Computer Science, Purdue University, West Lafayette, Indiana, United States of America.

Plos Computational Biology
|June 23, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel graph-based visualization for high-parameter flow cytometry data, improving biological interpretation and quantitative analysis beyond traditional methods.

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Last Updated: Jun 25, 2026

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Area of Science:

  • Computational Biology
  • Data Visualization
  • Immunology

Background:

  • Current single-cell analysis visualization methods (e.g., t-SNE, UMAP) struggle with high-parameter flow cytometry data.
  • These methods oversimplify biological complexity and lack quantitative analysis frameworks.

Purpose of the Study:

  • To develop a graph-based visualization framework for intuitive understanding and quantitative analysis of flow cytometry data.
  • To address limitations of conventional visualization techniques in high-parameter single-cell analysis.

Main Methods:

  • A graph-based framework using optimal transport theory (Sinkhorn distance) to define cell populations and quantify inter-population similarity.
  • Biologically consistent 2D graph layouts generated using phenotype-aware Hamming distance.
  • Customized graph-edit distance to characterize structural differences between sample graphs.

Main Results:

  • Demonstrated on clinical immunotherapy and acute myeloid leukemia flow cytometry datasets.
  • The framework provides robust, quantitative visual summaries of cell populations.
  • Enabled statistical analysis of graph edit distances for disease and treatment insights.

Conclusions:

  • The graph-based approach bridges the gap between flow cytometry data visualization and biological interpretation.
  • Offers a principled framework for downstream quantitative analysis and statistical insights.
  • Enhances understanding of disease progression and treatment response through improved data visualization.