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Proteintech γ h2 ax
LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and <t>γ-H2</t> AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups
γ H2 Ax, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 320 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/γ h2 ax/product/Proteintech
Average 96 stars, based on 320 article reviews
γ h2 ax - by Bioz Stars, 2026-04
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1) Product Images from "Identification of DNA damage and repair gene-related markers in pancreatic ductal adenocarcinoma by single-cell and bulk RNA sequencing"

Article Title: Identification of DNA damage and repair gene-related markers in pancreatic ductal adenocarcinoma by single-cell and bulk RNA sequencing

Journal: Discover Oncology

doi: 10.1007/s12672-025-02293-w

LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and γ-H2 AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups
Figure Legend Snippet: LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and γ-H2 AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups

Techniques Used: Immunohistochemical staining, Staining, Expressing, Knockdown



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LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and <t>γ-H2</t> AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups
γ H2 Ax, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and <t>γ-H2</t> AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups
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LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and <t>γ-H2</t> AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups
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LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and <t>γ-H2</t> AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups
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LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and <t>γ-H2</t> AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups
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LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and <t>γ-H2</t> AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups
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The ImageJ-based interface of the Focinator offers options to adapt the evaluation parameters to distinct image characteristics. Figure 1 shows ImageJ with the Focinator macro installed as start-up macro after opening a multi-channel image. This microscope image with the file format ZVI 16-bit includes three fluorescence channels. The main window of the Focinator is implemented into the ImageJ window. It consists of a menu ( 2 ), buttons ( 1 ) and Focinator Options ( 3 and 4 ). The Focinator Options windows offer several preferences for the user to adapt the macro’s behavior to individual requirements. Picture Settings: First step is to tell the macro, the input folder and if there is a multi-channel image or more single pictures will be opened. In the second step you choose in which channel the foci have to be counted and where the ROIs should be selected. In our example, the <t>γ-H2.AX</t> foci are in channel number 2 ( on top after opening the image ). The macro will use the setting “1st foci channel = front channel” for all pictures automatically. If no second foci channel is used the setting should be changed to “inactive”. ROI Settings ( 3 ): Depending on image quality, size and magnification, it is recommended to set the threshold and the size filters for ROIs. Alternatively, the choice of automated thresholding is possible. It is possible to exclude objects that are partially outside of the image. If there are objects to exclude because they are not circular enough or too small, it is possible to exclude them via circularity filters or size filters. “Use fill holes” should be activated, if the ROI selection left holes in the cells. Overlapping ROIs (cells, nuclei) might be separated by choosing “watershed”. Regarding the batch mode “check selection” offers the possibility of stopping during the selection process. “Invert images” should be checked when working with images with light background. For the automated batch ( 4 ) mode, output directories need to be chosen to save the results. An important step of evaluation is to choose the right noise level. Noise level values can be set independently in multi-channel analysis to exclude background artifacts. By defining the cut off, foci with intensities below a certain value are deleted, which excludes background noise. The value for area correction is dependent on the mean size of the analyzed nuclei. The factor corrects the foci number divided by the individual area of each nucleus. The usage of the percentile option enables the user to delete the outliers, such as cells with false γ-H2.AX foci induced by replication. Colocalization analyses are also possible. This option compares the localization of two foci in two different channels with a selectable tolerance
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Image Search Results


LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and γ-H2 AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups

Journal: Discover Oncology

Article Title: Identification of DNA damage and repair gene-related markers in pancreatic ductal adenocarcinoma by single-cell and bulk RNA sequencing

doi: 10.1007/s12672-025-02293-w

Figure Lengend Snippet: LY6D affects DNA damage repair and proliferation in PDAC cells. A Immunohistochemical staining was used to detect the expression of LY6D in PDAC tissues and adjacent tissues. The dotted diagram shows a significant increase in LY6D expression in PDAC tissues compared to normal tissues (p < 0.0001). B IHC scores for each tissue type. C qPCR results showing the knockdown efficiency of LY6D in SW1990 cells and PATU- 8988 T cells. D , E Co-staining of 53BP1 and γ-H2 AX confirmed that LY6D knockdown induces DSBs, with colocalized foci observed in both SW1990 and PATU- 8988 T cells. F – H EdU assays demonstrated the proliferation ability of different SW1990 and PATU- 8988 T treatment groups

Article Snippet: A mouse monoclonal antibody (1:200) against γ-H2 AX and a rabbit monoclonal antibody (1:200) against TP53BP1-Specific antibody (83,809–1-RR, Proteintech) were then added to the cells, which were then incubated for 1 h at room temperature.

Techniques: Immunohistochemical staining, Staining, Expressing, Knockdown

The ImageJ-based interface of the Focinator offers options to adapt the evaluation parameters to distinct image characteristics. Figure 1 shows ImageJ with the Focinator macro installed as start-up macro after opening a multi-channel image. This microscope image with the file format ZVI 16-bit includes three fluorescence channels. The main window of the Focinator is implemented into the ImageJ window. It consists of a menu ( 2 ), buttons ( 1 ) and Focinator Options ( 3 and 4 ). The Focinator Options windows offer several preferences for the user to adapt the macro’s behavior to individual requirements. Picture Settings: First step is to tell the macro, the input folder and if there is a multi-channel image or more single pictures will be opened. In the second step you choose in which channel the foci have to be counted and where the ROIs should be selected. In our example, the γ-H2.AX foci are in channel number 2 ( on top after opening the image ). The macro will use the setting “1st foci channel = front channel” for all pictures automatically. If no second foci channel is used the setting should be changed to “inactive”. ROI Settings ( 3 ): Depending on image quality, size and magnification, it is recommended to set the threshold and the size filters for ROIs. Alternatively, the choice of automated thresholding is possible. It is possible to exclude objects that are partially outside of the image. If there are objects to exclude because they are not circular enough or too small, it is possible to exclude them via circularity filters or size filters. “Use fill holes” should be activated, if the ROI selection left holes in the cells. Overlapping ROIs (cells, nuclei) might be separated by choosing “watershed”. Regarding the batch mode “check selection” offers the possibility of stopping during the selection process. “Invert images” should be checked when working with images with light background. For the automated batch ( 4 ) mode, output directories need to be chosen to save the results. An important step of evaluation is to choose the right noise level. Noise level values can be set independently in multi-channel analysis to exclude background artifacts. By defining the cut off, foci with intensities below a certain value are deleted, which excludes background noise. The value for area correction is dependent on the mean size of the analyzed nuclei. The factor corrects the foci number divided by the individual area of each nucleus. The usage of the percentile option enables the user to delete the outliers, such as cells with false γ-H2.AX foci induced by replication. Colocalization analyses are also possible. This option compares the localization of two foci in two different channels with a selectable tolerance

Journal: Radiation Oncology (London, England)

Article Title: The Focinator - a new open-source tool for high-throughput foci evaluation of DNA damage

doi: 10.1186/s13014-015-0453-1

Figure Lengend Snippet: The ImageJ-based interface of the Focinator offers options to adapt the evaluation parameters to distinct image characteristics. Figure 1 shows ImageJ with the Focinator macro installed as start-up macro after opening a multi-channel image. This microscope image with the file format ZVI 16-bit includes three fluorescence channels. The main window of the Focinator is implemented into the ImageJ window. It consists of a menu ( 2 ), buttons ( 1 ) and Focinator Options ( 3 and 4 ). The Focinator Options windows offer several preferences for the user to adapt the macro’s behavior to individual requirements. Picture Settings: First step is to tell the macro, the input folder and if there is a multi-channel image or more single pictures will be opened. In the second step you choose in which channel the foci have to be counted and where the ROIs should be selected. In our example, the γ-H2.AX foci are in channel number 2 ( on top after opening the image ). The macro will use the setting “1st foci channel = front channel” for all pictures automatically. If no second foci channel is used the setting should be changed to “inactive”. ROI Settings ( 3 ): Depending on image quality, size and magnification, it is recommended to set the threshold and the size filters for ROIs. Alternatively, the choice of automated thresholding is possible. It is possible to exclude objects that are partially outside of the image. If there are objects to exclude because they are not circular enough or too small, it is possible to exclude them via circularity filters or size filters. “Use fill holes” should be activated, if the ROI selection left holes in the cells. Overlapping ROIs (cells, nuclei) might be separated by choosing “watershed”. Regarding the batch mode “check selection” offers the possibility of stopping during the selection process. “Invert images” should be checked when working with images with light background. For the automated batch ( 4 ) mode, output directories need to be chosen to save the results. An important step of evaluation is to choose the right noise level. Noise level values can be set independently in multi-channel analysis to exclude background artifacts. By defining the cut off, foci with intensities below a certain value are deleted, which excludes background noise. The value for area correction is dependent on the mean size of the analyzed nuclei. The factor corrects the foci number divided by the individual area of each nucleus. The usage of the percentile option enables the user to delete the outliers, such as cells with false γ-H2.AX foci induced by replication. Colocalization analyses are also possible. This option compares the localization of two foci in two different channels with a selectable tolerance

Article Snippet: Antibodies linked with Alexa Fluor 647 against γ-H2.AX protein were obtained from Becton Dickinson (Heidelberg, Germany).

Techniques: Microscopy, Fluorescence, Selection

Use of the Focinator macro reduces counting times compared to ImageJ-based counting and manual evaluation. TRAMP-C1 cells were irradiated with 3 Gy. The cells were fixed and permeabilized for 15 min with 3 % PFA and 0.2 % Triton X-100 at different time points after irradiation. The nuclei were stained with Hoechst 33342. DSB foci were labeled with Alexa Fluor 647-linked anti- γ-H2.AX antibodies. The evaluation time for the same 35 multi-channel images containing 439 nuclei was compared between the analysis with the Focinator, ImageJ-based counting via manual ROI marking and “ Find Maxima… ” function or manual counting. a Evaluation times using the different counting methods. b Comparison of detected nuclei numbers by ImageJ-based analysis, Focinator batch mode and manual counting shown as overall ROI count

Journal: Radiation Oncology (London, England)

Article Title: The Focinator - a new open-source tool for high-throughput foci evaluation of DNA damage

doi: 10.1186/s13014-015-0453-1

Figure Lengend Snippet: Use of the Focinator macro reduces counting times compared to ImageJ-based counting and manual evaluation. TRAMP-C1 cells were irradiated with 3 Gy. The cells were fixed and permeabilized for 15 min with 3 % PFA and 0.2 % Triton X-100 at different time points after irradiation. The nuclei were stained with Hoechst 33342. DSB foci were labeled with Alexa Fluor 647-linked anti- γ-H2.AX antibodies. The evaluation time for the same 35 multi-channel images containing 439 nuclei was compared between the analysis with the Focinator, ImageJ-based counting via manual ROI marking and “ Find Maxima… ” function or manual counting. a Evaluation times using the different counting methods. b Comparison of detected nuclei numbers by ImageJ-based analysis, Focinator batch mode and manual counting shown as overall ROI count

Article Snippet: Antibodies linked with Alexa Fluor 647 against γ-H2.AX protein were obtained from Becton Dickinson (Heidelberg, Germany).

Techniques: Irradiation, Staining, Labeling

The Focinator’s accuracy is comparable to manual counting and evaluation only with ImageJ. ImageJ-based, manual counting and the usage of the Focinator macro were compared. To evaluate the repair time-dependent decrease of γ-H2.AX foci after irradiation TRAMP-C1 cells were irradiated with 3 Gy, incubated at 37 °C and fixed 0.5, 1, 2, 4, 6 and 24 h after irradiation. The cells were permeabilized and stained with an Alexa 647-linked anti- γ-H2.AX antibody. A total number of approximately 40 nuclei per time point was evaluated. a Development of the mean foci count per nucleus form three independent experiments at stated time points after irradiation. b A dose response curve depicts foci count after different doses (0.5, 1.5 and 3 Gy) 30 min after irradiation. A direct correlation between the different scoring methods with respective correlations value (R 2 ) at the time points 0.5, 1, 2, 4, 6 and 24 h after irradiation is shown for Focinator-based evaluation in comparison to using ImageJ alone in ( c ) and compared to manual counting in ( d )

Journal: Radiation Oncology (London, England)

Article Title: The Focinator - a new open-source tool for high-throughput foci evaluation of DNA damage

doi: 10.1186/s13014-015-0453-1

Figure Lengend Snippet: The Focinator’s accuracy is comparable to manual counting and evaluation only with ImageJ. ImageJ-based, manual counting and the usage of the Focinator macro were compared. To evaluate the repair time-dependent decrease of γ-H2.AX foci after irradiation TRAMP-C1 cells were irradiated with 3 Gy, incubated at 37 °C and fixed 0.5, 1, 2, 4, 6 and 24 h after irradiation. The cells were permeabilized and stained with an Alexa 647-linked anti- γ-H2.AX antibody. A total number of approximately 40 nuclei per time point was evaluated. a Development of the mean foci count per nucleus form three independent experiments at stated time points after irradiation. b A dose response curve depicts foci count after different doses (0.5, 1.5 and 3 Gy) 30 min after irradiation. A direct correlation between the different scoring methods with respective correlations value (R 2 ) at the time points 0.5, 1, 2, 4, 6 and 24 h after irradiation is shown for Focinator-based evaluation in comparison to using ImageJ alone in ( c ) and compared to manual counting in ( d )

Article Snippet: Antibodies linked with Alexa Fluor 647 against γ-H2.AX protein were obtained from Becton Dickinson (Heidelberg, Germany).

Techniques: Irradiation, Incubation, Staining