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ivis spectrum system  (Revvity)


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    Revvity ivis spectrum system
    CD169+ macrophages repress tumor progression in liver. (A-D) B16-F10 melanoma cells grew faster in CD169-DTR mice. (A) Experimental design. (B) Growth of tumors was examined using in vivo imaging system by evaluating abdominal fluorescence signals. The average radiance of two groups were compared. Two-way ANOVA with Sidak's multiple comparisons test. (C) The livers bearing with metastatic tumors were harvested (left panel). The number of tumors in each liver were counted (right panel). (D) Representative H&E staining of liver tissues. Scale bar, 200μm, 50μm. The data were from one experiment representative of two independent experiments. (E-G) Transfer of CD169+ macrophages inhibits B16-F10 melanoma cells growth in CD169-DTR mice. (E) Experiment design (n = 3∼4 per group). (F) The abdominal fluorescence signals were examined with in vivo imaging system. The average radiance of two groups were compared. (G) The livers were harvested from the mice receiving CD169+ macrophages or vehicle, and number of tumors were counted.
    Ivis Spectrum System, supplied by Revvity, used in various techniques. Bioz Stars score: 96/100, based on 34889 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/execution+platform/pmc08662336-57-25-28?v=Revvity
    Average 96 stars, based on 34889 article reviews
    ivis spectrum system - by Bioz Stars, 2026-07
    96/100 stars

    Images

    1) Product Images from "CD169-positive macrophages enhance abscopal effect of radiofrequency ablation therapy in liver cancer"

    Article Title: CD169-positive macrophages enhance abscopal effect of radiofrequency ablation therapy in liver cancer

    Journal: Translational Oncology

    doi: 10.1016/j.tranon.2021.101306

    CD169+ macrophages repress tumor progression in liver. (A-D) B16-F10 melanoma cells grew faster in CD169-DTR mice. (A) Experimental design. (B) Growth of tumors was examined using in vivo imaging system by evaluating abdominal fluorescence signals. The average radiance of two groups were compared. Two-way ANOVA with Sidak's multiple comparisons test. (C) The livers bearing with metastatic tumors were harvested (left panel). The number of tumors in each liver were counted (right panel). (D) Representative H&E staining of liver tissues. Scale bar, 200μm, 50μm. The data were from one experiment representative of two independent experiments. (E-G) Transfer of CD169+ macrophages inhibits B16-F10 melanoma cells growth in CD169-DTR mice. (E) Experiment design (n = 3∼4 per group). (F) The abdominal fluorescence signals were examined with in vivo imaging system. The average radiance of two groups were compared. (G) The livers were harvested from the mice receiving CD169+ macrophages or vehicle, and number of tumors were counted.
    Figure Legend Snippet: CD169+ macrophages repress tumor progression in liver. (A-D) B16-F10 melanoma cells grew faster in CD169-DTR mice. (A) Experimental design. (B) Growth of tumors was examined using in vivo imaging system by evaluating abdominal fluorescence signals. The average radiance of two groups were compared. Two-way ANOVA with Sidak's multiple comparisons test. (C) The livers bearing with metastatic tumors were harvested (left panel). The number of tumors in each liver were counted (right panel). (D) Representative H&E staining of liver tissues. Scale bar, 200μm, 50μm. The data were from one experiment representative of two independent experiments. (E-G) Transfer of CD169+ macrophages inhibits B16-F10 melanoma cells growth in CD169-DTR mice. (E) Experiment design (n = 3∼4 per group). (F) The abdominal fluorescence signals were examined with in vivo imaging system. The average radiance of two groups were compared. (G) The livers were harvested from the mice receiving CD169+ macrophages or vehicle, and number of tumors were counted.

    Techniques Used: In Vivo Imaging, Fluorescence, Staining



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    Image Search Results


    Controller model for an inverted pendulum integrated within the Simulink environment. Input data of the controller are visible in the design window and can be changed without the need to access the CPAL model. The output data are updated by the CPAL controler. The controller model is written in CPAL and executed by an interpreter embedded in the controller block. The ast file format is the more-compact binary equivalent form of the source-code controller model.

    Journal: Sensors (Basel, Switzerland)

    Article Title: A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

    doi: 10.3390/s18020628

    Figure Lengend Snippet: Controller model for an inverted pendulum integrated within the Simulink environment. Input data of the controller are visible in the design window and can be changed without the need to access the CPAL model. The output data are updated by the CPAL controler. The controller model is written in CPAL and executed by an interpreter embedded in the controller block. The ast file format is the more-compact binary equivalent form of the source-code controller model.

    Article Snippet: We provide the CPAL execution platform for Simulink as open access for experimentation.

    Techniques: Blocking Assay

    Illustration of a CPAL controller in Simulink. Here, the CPAL model controls the servo which in turn actuates the engine throttle. The controller task is executed with simulated input-to-output delays.

    Journal: Sensors (Basel, Switzerland)

    Article Title: A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

    doi: 10.3390/s18020628

    Figure Lengend Snippet: Illustration of a CPAL controller in Simulink. Here, the CPAL model controls the servo which in turn actuates the engine throttle. The controller task is executed with simulated input-to-output delays.

    Article Snippet: We provide the CPAL execution platform for Simulink as open access for experimentation.

    Techniques: