Data Sheet 2_The effect of training intervention based on health belief model on self-care behaviors of women with gestational diabetes mellitus.pdf by Fatemeh Mohammadkhah (14157844)

“…Also, the comparison of averages of blood sugar levels after the intervention in the two groups indicated that fasting blood sugar level, A1C hemoglobin, and blood sugar levels measured 2 h after the meal significantly decreased in the intervention group (p < 0.001). …”

Vasculogenic mimicry in melanoma tissue : immunohistochemistry, cell growth & morphological assays, migration & invasion assays and protein expression analyses by Rakolote Matlala (11071533)

“…Western blot analysis confirmed VEGFR-1 expression in melanoma cells, and VEGFR-1 blockade significantly reduced migration and invasion, reinforcing its role in vasculogenic mimicry.…”

Table 2_Down-regulation of colon mucin production induced by Eimeria pragensis infection in mice.xlsx by Yulia Dwi Setia (21590591)

“…Maximal parasite accumulation in the proximal colon was observed at 8 dpi in histological examination as well as qPCR. Colon length was significantly shortened at 3 dpi. Goblet cell area significantly reduced at 8 dpi (p < 0.05). …”

Experiment 2, trial D. by Ottavia Benedicenti (9100619)

Data Sheet 3_Identification of telomere-related gene subtypes and prognostic signatures in osteosarcoma.xlsx by Zhaoguang Song (20778602)

“…The scores of stromal, immune and ESTIMATES were observably increased, and tumor purity was decreased in C1 subtypes compared to C2 subtypes. Differentially expressed genes between C1 and C2 were highly enriched in immune-related pathways. …”

Data Sheet 2_Identification of telomere-related gene subtypes and prognostic signatures in osteosarcoma.xlsx by Zhaoguang Song (20778602)

“…The scores of stromal, immune and ESTIMATES were observably increased, and tumor purity was decreased in C1 subtypes compared to C2 subtypes. Differentially expressed genes between C1 and C2 were highly enriched in immune-related pathways. …”

Table 5_Ten-year outcomes of repeat keratoplasty for optical indications.docx by Victoria Grace Dimacali (20597690)

“…Cox multiple regression analysis showed male gender (p = 0.023), PK regraft (p = 0.003), regraft rejection (p = 0.003), and initial graft indications of pseudophakic bullous keratopathy (p = 0.005) and aphakic bullous keratopathy (p = 0.004) to be risk factors for regraft failure, while longer time to regraft was associated with decreased risk of failure (p = 0.013).</p>Conclusion<p>Performing EK for failed optical PK or EK significantly improved regraft survival compared to repeat PK. …”

Table 2_Ten-year outcomes of repeat keratoplasty for optical indications.docx by Victoria Grace Dimacali (20597690)

“…Cox multiple regression analysis showed male gender (p = 0.023), PK regraft (p = 0.003), regraft rejection (p = 0.003), and initial graft indications of pseudophakic bullous keratopathy (p = 0.005) and aphakic bullous keratopathy (p = 0.004) to be risk factors for regraft failure, while longer time to regraft was associated with decreased risk of failure (p = 0.013).</p>Conclusion<p>Performing EK for failed optical PK or EK significantly improved regraft survival compared to repeat PK. …”

Table 3_Ten-year outcomes of repeat keratoplasty for optical indications.docx by Victoria Grace Dimacali (20597690)

“…Cox multiple regression analysis showed male gender (p = 0.023), PK regraft (p = 0.003), regraft rejection (p = 0.003), and initial graft indications of pseudophakic bullous keratopathy (p = 0.005) and aphakic bullous keratopathy (p = 0.004) to be risk factors for regraft failure, while longer time to regraft was associated with decreased risk of failure (p = 0.013).</p>Conclusion<p>Performing EK for failed optical PK or EK significantly improved regraft survival compared to repeat PK. …”

Table 4_Ten-year outcomes of repeat keratoplasty for optical indications.docx by Victoria Grace Dimacali (20597690)

“…Cox multiple regression analysis showed male gender (p = 0.023), PK regraft (p = 0.003), regraft rejection (p = 0.003), and initial graft indications of pseudophakic bullous keratopathy (p = 0.005) and aphakic bullous keratopathy (p = 0.004) to be risk factors for regraft failure, while longer time to regraft was associated with decreased risk of failure (p = 0.013).</p>Conclusion<p>Performing EK for failed optical PK or EK significantly improved regraft survival compared to repeat PK. …”

Image 3_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Table 3_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Table 8_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Table 2_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Image 2_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Table 6_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Table 5_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Image 5_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Table 7_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”

Table 4_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…Cell–cell communication analysis revealed extensive signaling pathways (e.g., LAMININ and COLLAGEN) activated in EF cells under AF conditions, in addition to the specific activation of MK signaling in AF. It also uncovered a loss of certain EC signals (e.g., GRN–SORT1 and AGRN–DAG1) in AF and a marked reduction in NPPA–NPR1 signaling from SMC to EC. …”