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Related Concept Videos

Diffusion01:12

Diffusion

176.8K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
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Diffusion01:21

Diffusion

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Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
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Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

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Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
When administered orally, drugs establish a substantial concentration gradient between the gastrointestinal (GI) lumen and the bloodstream, expediting...
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Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

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Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
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Transcription Attenuation in Prokaryotes02:42

Transcription Attenuation in Prokaryotes

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Transcriptional attenuation occurs when RNA transcription is prematurely terminated due to the formation of a terminator mRNA hairpin structure.  Bacteria use these hairpins to regulate the transcription process and control the synthesis of several amino acids including histidine, lysine, threonine, and phenylalanine. Transcription attenuation takes place in the non-coding regions of mRNA.
There are several different mechanisms used to attenuate transcription. In ribosome mediated...
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Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

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Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
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Updated: May 7, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
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DiffuST: a Latent Diffusion Model for Spatial Transcriptomics Denoising.

Shaoqing Jiao, Dazhi Lu, Xi Zeng

    IEEE Transactions on Computational Biology and Bioinformatics
    |May 5, 2026
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    Summary
    This summary is machine-generated.

    We developed DiffuST, a novel method using latent diffusion models to denoise spatial transcriptomics data. This approach enhances biological signal clarity and improves downstream analysis for deeper biological insights.

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    Area of Science:

    • Genomics
    • Bioinformatics
    • Computational Biology

    Background:

    • Spatial transcriptomics technologies offer gene expression profiling with spatial context.
    • Noise from low RNA capture and experimental steps can obscure biological signals.
    • Existing denoising methods may not fully address spatial transcriptomics data complexities.

    Purpose of the Study:

    • To develop an advanced computational method for denoising spatial transcriptomics data.
    • To improve the accuracy and interpretability of spatial transcriptomics analyses.
    • To leverage pathology images alongside gene expression data for enhanced denoising.

    Main Methods:

    • Development of DiffuST, a latent diffusion model tailored for spatial transcriptomics.
    • Integration of a graph autoencoder for multi-scale feature extraction.
    • Utilizing pre-trained models and pathology images to guide the denoising process.
    • Mapping multi-scale features into a shared latent space for effective noise reduction.

    Main Results:

    • DiffuST demonstrated superior performance compared to existing denoising methods across multiple datasets.
    • The method effectively reduced noise while preserving crucial biological signals.
    • Denoised data from DiffuST led to enhanced downstream spatial transcriptomics analyses.
    • Significant biological insights were uncovered using the denoised data.

    Conclusions:

    • DiffuST provides a powerful new tool for denoising spatial transcriptomics data.
    • The method improves the reliability and biological interpretability of spatial transcriptomics studies.
    • DiffuST has the potential to advance discoveries in various biological fields utilizing spatial omics.