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the spatially resolved metabolomics platform  (MetWare Ltd)

 
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    MetWare Ltd the spatially resolved metabolomics platform
    The design and workflow of this study. This study mainly contained four parts. First, 68 patients with unilateral or bilateral DFUs were treated with TTT surgery, and samples at six key time points were collected for the study. Second, label-free proteomic analysis of immunomodulatory proteins and regulatory pathways ( N =30, TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ) was performed. Third, skin tissue samples from three key time points were collected for spatial <t>metabolomics</t> to validate the immunological metabolites ( N =7, TTT 0 , TTT 14, and TTT 21 ). Next, the specific immune biomarkers were validated in the clinical laboratory (TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ). In addition, transcriptomics analysis for skin tissue samples was applied to screen out differential genes and signal pathways in regulating the immune response and wound healing ( N =3, TTT 0 , TTT 14 , and TTT 21 ). Finally, the integration of data from multiomic and clinical immune biomarker analyses was applied to investigate possible immune responses. N, the number of patients; TTT 0 , 1 day before the TTT external fixator was fixed; TTT 3 , 3 days after the TTT external fixator was fixed; TTT 7 , 7 days after the TTT external fixator was fixed; TTT 14 , the day at which the upward movement was completed; TTT 21 , the day at which the downward transfer was completed; TTT 35 , the second day after the TTT external fixator was removed. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.
    The Spatially Resolved Metabolomics Platform, supplied by MetWare Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/the spatially resolved metabolomics platform/product/MetWare Ltd
    Average 90 stars, based on 1 article reviews
    the spatially resolved metabolomics platform - by Bioz Stars, 2026-04
    90/100 stars

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    1) Product Images from "Tibial cortex transverse transport surgery improves wound healing in patients with severe type 2 DFUs by activating a systemic immune response: a cross-sectional study"

    Article Title: Tibial cortex transverse transport surgery improves wound healing in patients with severe type 2 DFUs by activating a systemic immune response: a cross-sectional study

    Journal: International Journal of Surgery (London, England)

    doi: 10.1097/JS9.0000000000001897

    The design and workflow of this study. This study mainly contained four parts. First, 68 patients with unilateral or bilateral DFUs were treated with TTT surgery, and samples at six key time points were collected for the study. Second, label-free proteomic analysis of immunomodulatory proteins and regulatory pathways ( N =30, TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ) was performed. Third, skin tissue samples from three key time points were collected for spatial metabolomics to validate the immunological metabolites ( N =7, TTT 0 , TTT 14, and TTT 21 ). Next, the specific immune biomarkers were validated in the clinical laboratory (TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ). In addition, transcriptomics analysis for skin tissue samples was applied to screen out differential genes and signal pathways in regulating the immune response and wound healing ( N =3, TTT 0 , TTT 14 , and TTT 21 ). Finally, the integration of data from multiomic and clinical immune biomarker analyses was applied to investigate possible immune responses. N, the number of patients; TTT 0 , 1 day before the TTT external fixator was fixed; TTT 3 , 3 days after the TTT external fixator was fixed; TTT 7 , 7 days after the TTT external fixator was fixed; TTT 14 , the day at which the upward movement was completed; TTT 21 , the day at which the downward transfer was completed; TTT 35 , the second day after the TTT external fixator was removed. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.
    Figure Legend Snippet: The design and workflow of this study. This study mainly contained four parts. First, 68 patients with unilateral or bilateral DFUs were treated with TTT surgery, and samples at six key time points were collected for the study. Second, label-free proteomic analysis of immunomodulatory proteins and regulatory pathways ( N =30, TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ) was performed. Third, skin tissue samples from three key time points were collected for spatial metabolomics to validate the immunological metabolites ( N =7, TTT 0 , TTT 14, and TTT 21 ). Next, the specific immune biomarkers were validated in the clinical laboratory (TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ). In addition, transcriptomics analysis for skin tissue samples was applied to screen out differential genes and signal pathways in regulating the immune response and wound healing ( N =3, TTT 0 , TTT 14 , and TTT 21 ). Finally, the integration of data from multiomic and clinical immune biomarker analyses was applied to investigate possible immune responses. N, the number of patients; TTT 0 , 1 day before the TTT external fixator was fixed; TTT 3 , 3 days after the TTT external fixator was fixed; TTT 7 , 7 days after the TTT external fixator was fixed; TTT 14 , the day at which the upward movement was completed; TTT 21 , the day at which the downward transfer was completed; TTT 35 , the second day after the TTT external fixator was removed. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.

    Techniques Used: Biomarker Assay

    Spatially resolved metabolomics analysis of DFU skin tissues. (A) Crucial processing of skin tissue samples for spatial metabolomics analysis, including H&E staining of skin tissue sections, DHB matrix spraying of frozen sections, and metabolite spatial distribution with Gaussian smoothing. (B and C) OPLS-DA of spatial metabolomics datasets. (D–F) Representative mass spectra of DFU skin tissue (TTT 0 , TTT 14 , and TTT 21 ). (G–I) The bar diagram shows the expression levels of differentially abundant metabolites in glycerophospholipid, fatty acid, and glycerophospholipid metabolism pathways at TTT 14 and TTT 21 compared with TTT 0 . A total of eight differentially abundant metabolites were identified in TTT 0 , TTT 14 , and TTT 21 , and their change trends were statistically analyzed. (J–L) Bar plot of KEGG pathway enrichment analysis for the differentially abundant metabolites. The glycerophospholipid metabolism pathway was validated in DFU skin tissues. ** P value <0.005; * P value <0.05. DFU, diabetic foot ulceration; KEGG, Kyoto Encyclopedia of Genes and Genomes; TTT, tibial cortex transverse transport.
    Figure Legend Snippet: Spatially resolved metabolomics analysis of DFU skin tissues. (A) Crucial processing of skin tissue samples for spatial metabolomics analysis, including H&E staining of skin tissue sections, DHB matrix spraying of frozen sections, and metabolite spatial distribution with Gaussian smoothing. (B and C) OPLS-DA of spatial metabolomics datasets. (D–F) Representative mass spectra of DFU skin tissue (TTT 0 , TTT 14 , and TTT 21 ). (G–I) The bar diagram shows the expression levels of differentially abundant metabolites in glycerophospholipid, fatty acid, and glycerophospholipid metabolism pathways at TTT 14 and TTT 21 compared with TTT 0 . A total of eight differentially abundant metabolites were identified in TTT 0 , TTT 14 , and TTT 21 , and their change trends were statistically analyzed. (J–L) Bar plot of KEGG pathway enrichment analysis for the differentially abundant metabolites. The glycerophospholipid metabolism pathway was validated in DFU skin tissues. ** P value <0.005; * P value <0.05. DFU, diabetic foot ulceration; KEGG, Kyoto Encyclopedia of Genes and Genomes; TTT, tibial cortex transverse transport.

    Techniques Used: Staining, Expressing

    Spatial expression images of differentially abundant metabolites in DFU tissue sections based on spatially resolved metabolomics data (intensity in color scale is relative value). (A) Expression and spatial distributions of theobromine, levocarnitine propionate, canthaxanthin A, and triacetin at TTT 14 compared with those at TTT 0 . (B) Expression and spatial distributions of elemonic acid and camelliagenin at TTT 21 compared with those at TTT 0 . (C) Decreased concentrations of L-palmitoylcarnitine and stearoylcarnitine in DFU tissues from TTT 14 and TTT 21 patients compared with those of TTT 0 patients. * P value <0.05, ** P value <0.01. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.
    Figure Legend Snippet: Spatial expression images of differentially abundant metabolites in DFU tissue sections based on spatially resolved metabolomics data (intensity in color scale is relative value). (A) Expression and spatial distributions of theobromine, levocarnitine propionate, canthaxanthin A, and triacetin at TTT 14 compared with those at TTT 0 . (B) Expression and spatial distributions of elemonic acid and camelliagenin at TTT 21 compared with those at TTT 0 . (C) Decreased concentrations of L-palmitoylcarnitine and stearoylcarnitine in DFU tissues from TTT 14 and TTT 21 patients compared with those of TTT 0 patients. * P value <0.05, ** P value <0.01. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.

    Techniques Used: Expressing



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    the spatially resolved metabolomics platform  (MetWare Ltd)
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    MetWare Ltd the spatially resolved metabolomics platform
    The design and workflow of this study. This study mainly contained four parts. First, 68 patients with unilateral or bilateral DFUs were treated with TTT surgery, and samples at six key time points were collected for the study. Second, label-free proteomic analysis of immunomodulatory proteins and regulatory pathways ( N =30, TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ) was performed. Third, skin tissue samples from three key time points were collected for spatial <t>metabolomics</t> to validate the immunological metabolites ( N =7, TTT 0 , TTT 14, and TTT 21 ). Next, the specific immune biomarkers were validated in the clinical laboratory (TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ). In addition, transcriptomics analysis for skin tissue samples was applied to screen out differential genes and signal pathways in regulating the immune response and wound healing ( N =3, TTT 0 , TTT 14 , and TTT 21 ). Finally, the integration of data from multiomic and clinical immune biomarker analyses was applied to investigate possible immune responses. N, the number of patients; TTT 0 , 1 day before the TTT external fixator was fixed; TTT 3 , 3 days after the TTT external fixator was fixed; TTT 7 , 7 days after the TTT external fixator was fixed; TTT 14 , the day at which the upward movement was completed; TTT 21 , the day at which the downward transfer was completed; TTT 35 , the second day after the TTT external fixator was removed. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.
    The Spatially Resolved Metabolomics Platform, supplied by MetWare Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/the spatially resolved metabolomics platform/product/MetWare Ltd
    Average 90 stars, based on 1 article reviews
    the spatially resolved metabolomics platform - by Bioz Stars, 2026-04
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    The design and workflow of this study. This study mainly contained four parts. First, 68 patients with unilateral or bilateral DFUs were treated with TTT surgery, and samples at six key time points were collected for the study. Second, label-free proteomic analysis of immunomodulatory proteins and regulatory pathways ( N =30, TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ) was performed. Third, skin tissue samples from three key time points were collected for spatial metabolomics to validate the immunological metabolites ( N =7, TTT 0 , TTT 14, and TTT 21 ). Next, the specific immune biomarkers were validated in the clinical laboratory (TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ). In addition, transcriptomics analysis for skin tissue samples was applied to screen out differential genes and signal pathways in regulating the immune response and wound healing ( N =3, TTT 0 , TTT 14 , and TTT 21 ). Finally, the integration of data from multiomic and clinical immune biomarker analyses was applied to investigate possible immune responses. N, the number of patients; TTT 0 , 1 day before the TTT external fixator was fixed; TTT 3 , 3 days after the TTT external fixator was fixed; TTT 7 , 7 days after the TTT external fixator was fixed; TTT 14 , the day at which the upward movement was completed; TTT 21 , the day at which the downward transfer was completed; TTT 35 , the second day after the TTT external fixator was removed. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.

    Journal: International Journal of Surgery (London, England)

    Article Title: Tibial cortex transverse transport surgery improves wound healing in patients with severe type 2 DFUs by activating a systemic immune response: a cross-sectional study

    doi: 10.1097/JS9.0000000000001897

    Figure Lengend Snippet: The design and workflow of this study. This study mainly contained four parts. First, 68 patients with unilateral or bilateral DFUs were treated with TTT surgery, and samples at six key time points were collected for the study. Second, label-free proteomic analysis of immunomodulatory proteins and regulatory pathways ( N =30, TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ) was performed. Third, skin tissue samples from three key time points were collected for spatial metabolomics to validate the immunological metabolites ( N =7, TTT 0 , TTT 14, and TTT 21 ). Next, the specific immune biomarkers were validated in the clinical laboratory (TTT 0 , TTT 3 , TTT 7 , TTT 14 , TTT 21 , and TTT 35 ). In addition, transcriptomics analysis for skin tissue samples was applied to screen out differential genes and signal pathways in regulating the immune response and wound healing ( N =3, TTT 0 , TTT 14 , and TTT 21 ). Finally, the integration of data from multiomic and clinical immune biomarker analyses was applied to investigate possible immune responses. N, the number of patients; TTT 0 , 1 day before the TTT external fixator was fixed; TTT 3 , 3 days after the TTT external fixator was fixed; TTT 7 , 7 days after the TTT external fixator was fixed; TTT 14 , the day at which the upward movement was completed; TTT 21 , the day at which the downward transfer was completed; TTT 35 , the second day after the TTT external fixator was removed. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.

    Article Snippet: The analytical platform used for proteomic analysis was from Dashuo Biotech Co. Ltd (Dalian, China), the spatially resolved metabolomics platform was from MetWare Co. Ltd (Wuhan, China), and the transcriptomics platform was from Kangxiang Biotechnology Co. Ltd (Shanghai, China).

    Techniques: Biomarker Assay

    Spatially resolved metabolomics analysis of DFU skin tissues. (A) Crucial processing of skin tissue samples for spatial metabolomics analysis, including H&E staining of skin tissue sections, DHB matrix spraying of frozen sections, and metabolite spatial distribution with Gaussian smoothing. (B and C) OPLS-DA of spatial metabolomics datasets. (D–F) Representative mass spectra of DFU skin tissue (TTT 0 , TTT 14 , and TTT 21 ). (G–I) The bar diagram shows the expression levels of differentially abundant metabolites in glycerophospholipid, fatty acid, and glycerophospholipid metabolism pathways at TTT 14 and TTT 21 compared with TTT 0 . A total of eight differentially abundant metabolites were identified in TTT 0 , TTT 14 , and TTT 21 , and their change trends were statistically analyzed. (J–L) Bar plot of KEGG pathway enrichment analysis for the differentially abundant metabolites. The glycerophospholipid metabolism pathway was validated in DFU skin tissues. ** P value <0.005; * P value <0.05. DFU, diabetic foot ulceration; KEGG, Kyoto Encyclopedia of Genes and Genomes; TTT, tibial cortex transverse transport.

    Journal: International Journal of Surgery (London, England)

    Article Title: Tibial cortex transverse transport surgery improves wound healing in patients with severe type 2 DFUs by activating a systemic immune response: a cross-sectional study

    doi: 10.1097/JS9.0000000000001897

    Figure Lengend Snippet: Spatially resolved metabolomics analysis of DFU skin tissues. (A) Crucial processing of skin tissue samples for spatial metabolomics analysis, including H&E staining of skin tissue sections, DHB matrix spraying of frozen sections, and metabolite spatial distribution with Gaussian smoothing. (B and C) OPLS-DA of spatial metabolomics datasets. (D–F) Representative mass spectra of DFU skin tissue (TTT 0 , TTT 14 , and TTT 21 ). (G–I) The bar diagram shows the expression levels of differentially abundant metabolites in glycerophospholipid, fatty acid, and glycerophospholipid metabolism pathways at TTT 14 and TTT 21 compared with TTT 0 . A total of eight differentially abundant metabolites were identified in TTT 0 , TTT 14 , and TTT 21 , and their change trends were statistically analyzed. (J–L) Bar plot of KEGG pathway enrichment analysis for the differentially abundant metabolites. The glycerophospholipid metabolism pathway was validated in DFU skin tissues. ** P value <0.005; * P value <0.05. DFU, diabetic foot ulceration; KEGG, Kyoto Encyclopedia of Genes and Genomes; TTT, tibial cortex transverse transport.

    Article Snippet: The analytical platform used for proteomic analysis was from Dashuo Biotech Co. Ltd (Dalian, China), the spatially resolved metabolomics platform was from MetWare Co. Ltd (Wuhan, China), and the transcriptomics platform was from Kangxiang Biotechnology Co. Ltd (Shanghai, China).

    Techniques: Staining, Expressing

    Spatial expression images of differentially abundant metabolites in DFU tissue sections based on spatially resolved metabolomics data (intensity in color scale is relative value). (A) Expression and spatial distributions of theobromine, levocarnitine propionate, canthaxanthin A, and triacetin at TTT 14 compared with those at TTT 0 . (B) Expression and spatial distributions of elemonic acid and camelliagenin at TTT 21 compared with those at TTT 0 . (C) Decreased concentrations of L-palmitoylcarnitine and stearoylcarnitine in DFU tissues from TTT 14 and TTT 21 patients compared with those of TTT 0 patients. * P value <0.05, ** P value <0.01. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.

    Journal: International Journal of Surgery (London, England)

    Article Title: Tibial cortex transverse transport surgery improves wound healing in patients with severe type 2 DFUs by activating a systemic immune response: a cross-sectional study

    doi: 10.1097/JS9.0000000000001897

    Figure Lengend Snippet: Spatial expression images of differentially abundant metabolites in DFU tissue sections based on spatially resolved metabolomics data (intensity in color scale is relative value). (A) Expression and spatial distributions of theobromine, levocarnitine propionate, canthaxanthin A, and triacetin at TTT 14 compared with those at TTT 0 . (B) Expression and spatial distributions of elemonic acid and camelliagenin at TTT 21 compared with those at TTT 0 . (C) Decreased concentrations of L-palmitoylcarnitine and stearoylcarnitine in DFU tissues from TTT 14 and TTT 21 patients compared with those of TTT 0 patients. * P value <0.05, ** P value <0.01. DFU, diabetic foot ulceration; TTT, tibial cortex transverse transport.

    Article Snippet: The analytical platform used for proteomic analysis was from Dashuo Biotech Co. Ltd (Dalian, China), the spatially resolved metabolomics platform was from MetWare Co. Ltd (Wuhan, China), and the transcriptomics platform was from Kangxiang Biotechnology Co. Ltd (Shanghai, China).

    Techniques: Expressing