Table 3_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”

Table 5_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.doc by Ting Wu (106368)

“…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”

Table 13_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.doc by Ting Wu (106368)

“…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”

Table 6_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”

Table 11_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”

Table 7_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”

Table 10_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”

Table 4_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”

Data Sheet 1_Multi-omics identification of a polyamine metabolism related signature for hepatocellular carcinoma and revealing tumor microenvironment characteristics.pdf by Yuexi Yu (21158744)

“…Immune cell infiltration was analyzed using the CIBERSORT algorithm. Finally, RT-qPCR experiments were conducted to validate the expression of key genes.…”

Table 1_Multi-omics identification of a polyamine metabolism related signature for hepatocellular carcinoma and revealing tumor microenvironment characteristics.xlsx by Yuexi Yu (21158744)

“…Immune cell infiltration was analyzed using the CIBERSORT algorithm. Finally, RT-qPCR experiments were conducted to validate the expression of key genes.…”

Table 2_Multi-omics identification of a polyamine metabolism related signature for hepatocellular carcinoma and revealing tumor microenvironment characteristics.xlsx by Yuexi Yu (21158744)

“…Immune cell infiltration was analyzed using the CIBERSORT algorithm. Finally, RT-qPCR experiments were conducted to validate the expression of key genes.…”

DataSheet1_Integration of transcriptomics and machine learning for insights into breast cancer: exploring lipid metabolism and immune interactions.docx by Xiaohan Chen (384089)

“…Our study revealed distinct biological functions and mutation landscapes between high-scoring and low-scoring patients. …”

Additional data for the polyanion sodium cathode materials dataset by Martin Hoffmann Petersen (13626778)

“…The Perdew-Burke-Ernzerhof (PBE) functional with Hubbard-U corrections were appliedwas utilized for all calculations. …”

DataSheet2_Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms.PDF by D. S. Bug (19791612)

“…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …”

DataSheet2_Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms.PDF by D. S. Bug (19791612)

“…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …”

Table 1_In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis.xlsx by Yuqi Liu (501183)

“…Quantifying the biomechanical properties of the meniscus is essential for understanding its role in knee joint function and pathology.</p>Methods<p>This study aimed to determine the biomechanical properties of the meniscus in patients with severe KOA using experimental mechanical testing and an inverse finite element analysis (iFEA) model. …”

DataSheet1_Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms.PDF by D. S. Bug (19791612)

“…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …”

Table 2_In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis.xlsx by Yuqi Liu (501183)

“…Quantifying the biomechanical properties of the meniscus is essential for understanding its role in knee joint function and pathology.</p>Methods<p>This study aimed to determine the biomechanical properties of the meniscus in patients with severe KOA using experimental mechanical testing and an inverse finite element analysis (iFEA) model. …”

DataSheet1_Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms.PDF by D. S. Bug (19791612)

“…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …”

Code by Baoqiang Chen (21099509)

“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”