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 Experiment Videos

Appendix: a model of plaque formation.

D A Kaplan, L Naumovski, B Rothschild

    Gene
    |April 1, 1981
    PubMed
    Summary
    This summary is machine-generated.

    Related Concept Videos

    You might also read

    Related Articles

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

    Sort by
    Same author

    Graduate Student Literature Review: Mitochondrial response to heat stress and its implications on dairy cattle bioenergetics, metabolism, and production.

    Journal of dairy science·2023
    Same author

    Invited review: Physiological and behavioral effects of heat stress in dairy cows.

    Journal of dairy science·2020
    Same author

    Response to adrenocorticotropic hormone or corticotrophin-releasing hormone and vasopressin in lactating cows fed an immunomodulatory supplement under thermoneutral or acute heat stress conditions.

    Journal of dairy science·2020
    Same author

    An evaluation of an immunomodulatory feed ingredient in heat-stressed lactating Holstein cows: Effects on hormonal, physiological, and production responses.

    Journal of dairy science·2018
    Same author

    Technical note: Method for isolation of the bovine sweat gland and conditions for in vitro culture.

    Journal of dairy science·2018
    Same author

    TRIENNIAL LACTATION SYMPOSIUM/BOLFA:Historical perspectives of lactation biology in the late 20th and early 21st centuries.

    Journal of animal science·2018
    Same journal

    Face/off: phase-specific modeling of lineage plasticity using near-patient models in genitourinary cancers.

    Gene·2026
    Same journal

    Hierarchical analysis of metabolic phenotype reveals distinct microbiota and circulatory transcriptome in metabolic dysfunction-associated steatotic liver disease.

    Gene·2026
    Same journal

    Mutation T71R enhanced the structural stability and functional activity of wild type superoxide dismutase cloned from soil metagenome.

    Gene·2026
    Same journal

    Reduced ATXN1 expression as an adverse prognostic indicator in Acute myeloid leukemia.

    Gene·2026
    Same journal

    Constructing regulatory networks of Rubisco post-translational modifications: a novel avenue for engineering environment adaptive plants.

    Gene·2026
    Same journal

    Traumatic brain injury enhances fracture healing by upregulating VNN1 to activate the Wnt/β-catenin signaling pathway.

    Gene·2026
    See all related articles

    New equations accurately model plaque formation in soft agar based on initial cell density. These calculations predict plaque size, lysed cells per plaque, and cumulative cell lysis, aligning with experimental data.

    Area of Science:

    • Microbiology
    • Biophysics

    Background:

    • Plaque formation assays in soft agar are crucial for quantifying viral or bacterial activity.
    • Existing models for plaque formation often rely on simplifying assumptions that may limit their accuracy.

    Purpose of the Study:

    • To derive and validate new equations for plaque formation in soft agar.
    • To enable accurate calculation of plaque characteristics based on initial cell density.

    Main Methods:

    • Development of mathematical equations based on plaque formation dynamics in soft agar.
    • Experimental validation of derived equations using soft agar assays.
    • Analysis of plaque size, cell lysis, and cumulative cell lysis as functions of initial indicator cell density (Do).

    Main Results:

    Related Experiment Videos

    • Derived equations successfully predict average plaque size as a function of initial cell density (Do).
    • Calculations accurately determine the number of cells lysed per plaque and cumulative cell lysis over time.
    • Experimental data showed strong agreement with the values predicted by the derived equations.

    Conclusions:

    • The new equations provide a robust framework for analyzing plaque formation in soft agar.
    • These equations offer a quantitative method to assess cell lysis dynamics based on initial cell density.
    • The validated model improves the understanding and prediction of plaque development in microbiological assays.