Showing 17,241 - 17,260 results of 18,582 for search 'significantly ((((lower decrease) OR (((we decrease) OR (a decrease))))) OR (linear decrease))', query time: 0.53s Refine Results
  1. 17241

    Repeat the detection experiment. by Yingying Liu (360782)

    Published 2025
    “…The research focuses on the advantages and problems of residual networks and depth-wise separable convolution modules, designs a new remote sensing image change detection model, and finally sets up experiments for verification. …”
  2. 17242

    Data Sheet 1_Impact of SARS-CoV-2 vaccination and of seasonal variations on the innate immune inflammatory response.pdf by Hend Jarras (13138641)

    Published 2025
    “…</p>Results<p>Our results show that IL-8 production after stimulation decreased after vaccination. In addition, the IL-8 response was significantly different depending on the season when the visit occurred, for both COVID-19 vaccinated and unvaccinated individuals.…”
  3. 17243

    Detection network structure with IRAU [34]. by Yingying Liu (360782)

    Published 2025
    “…The research focuses on the advantages and problems of residual networks and depth-wise separable convolution modules, designs a new remote sensing image change detection model, and finally sets up experiments for verification. …”
  4. 17244

    Ablation experiments of various block. by Yingying Liu (360782)

    Published 2025
    “…The research focuses on the advantages and problems of residual networks and depth-wise separable convolution modules, designs a new remote sensing image change detection model, and finally sets up experiments for verification. …”
  5. 17245

    Kappa coefficients for different algorithms. by Yingying Liu (360782)

    Published 2025
    “…The research focuses on the advantages and problems of residual networks and depth-wise separable convolution modules, designs a new remote sensing image change detection model, and finally sets up experiments for verification. …”
  6. 17246

    The structure of ASPP+ block. by Yingying Liu (360782)

    Published 2025
    “…The research focuses on the advantages and problems of residual networks and depth-wise separable convolution modules, designs a new remote sensing image change detection model, and finally sets up experiments for verification. …”
  7. 17247

    The structure of attention gate block [31]. by Yingying Liu (360782)

    Published 2025
    “…The research focuses on the advantages and problems of residual networks and depth-wise separable convolution modules, designs a new remote sensing image change detection model, and finally sets up experiments for verification. …”
  8. 17248

    Data Sheet 1_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.pdf by Mattia Dalle Nogare (22696022)

    Published 2025
    “…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”
  9. 17249

    Data Sheet 2_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.csv by Jiashuo Li (7865036)

    Published 2025
    “…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”
  10. 17250

    Image 2_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.jpeg by Jiashuo Li (7865036)

    Published 2025
    “…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”
  11. 17251

    Image 4_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.jpeg by Jiashuo Li (7865036)

    Published 2025
    “…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”
  12. 17252

    Image 3_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.jpeg by Jiashuo Li (7865036)

    Published 2025
    “…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”
  13. 17253

    Image 5_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.jpeg by Jiashuo Li (7865036)

    Published 2025
    “…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”
  14. 17254

    Data Sheet 2_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.pdf by Mattia Dalle Nogare (22696022)

    Published 2025
    “…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”
  15. 17255

    Table 2_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.xlsx by Mattia Dalle Nogare (22696022)

    Published 2025
    “…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”
  16. 17256

    Table 1_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.xlsx by Mattia Dalle Nogare (22696022)

    Published 2025
    “…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”
  17. 17257

    Table 1_Evolving landscape of female cancers along with attributable risk factors in China from 1990 to 2021, and projections to 2040.xlsx by Yali Han (4676677)

    Published 2025
    “…Background<p>Female cancers pose a significant health burden in China, and this study identified and projected epidemiological trends of these cancers.…”
  18. 17258

    Data Sheet 1_Evolving landscape of female cancers along with attributable risk factors in China from 1990 to 2021, and projections to 2040.pdf by Yali Han (4676677)

    Published 2025
    “…Background<p>Female cancers pose a significant health burden in China, and this study identified and projected epidemiological trends of these cancers.…”
  19. 17259

    Table 2_Evolving landscape of female cancers along with attributable risk factors in China from 1990 to 2021, and projections to 2040.xlsx by Yali Han (4676677)

    Published 2025
    “…Background<p>Female cancers pose a significant health burden in China, and this study identified and projected epidemiological trends of these cancers.…”
  20. 17260

    Table 3_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.xlsx by Mattia Dalle Nogare (22696022)

    Published 2025
    “…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”