Knockdown of CD133 in EH-CA1a and EH-CA1b cells reduced invasive potential and increased sensitivities to gemcitabine and radiation. by Jinghan Wang (286016)

“…(B) Knockdown of CD133 significantly decreased invasive cells in EH-CA1a and EH-CA1b cells; data is presented as the number of invasive cells in per field. …”

DataSheet_3_The influence of 17β-estradiol plus norethisterone acetate treatment on markers of glucose and insulin metabolism in women: a systematic review and meta-analysis of ran... by Weijuan Cui (15536306)

“…Thus, we aimed to examine the impact of the co-administration of 17β-estradiol and norethisterone acetate on glycated haemoglobin (HbA1c), fasting glucose, insulin and C-peptide concentrations in females by means of a systematic review and meta-analysis of randomized controlled trials (RCTs).…”

DataSheet_4_The influence of 17β-estradiol plus norethisterone acetate treatment on markers of glucose and insulin metabolism in women: a systematic review and meta-analysis of ran... by Weijuan Cui (15536306)

“…Thus, we aimed to examine the impact of the co-administration of 17β-estradiol and norethisterone acetate on glycated haemoglobin (HbA1c), fasting glucose, insulin and C-peptide concentrations in females by means of a systematic review and meta-analysis of randomized controlled trials (RCTs).…”

DataSheet_2_The influence of 17β-estradiol plus norethisterone acetate treatment on markers of glucose and insulin metabolism in women: a systematic review and meta-analysis of ran... by Weijuan Cui (15536306)

“…Thus, we aimed to examine the impact of the co-administration of 17β-estradiol and norethisterone acetate on glycated haemoglobin (HbA1c), fasting glucose, insulin and C-peptide concentrations in females by means of a systematic review and meta-analysis of randomized controlled trials (RCTs).…”

DataSheet_1_The influence of 17β-estradiol plus norethisterone acetate treatment on markers of glucose and insulin metabolism in women: a systematic review and meta-analysis of ran... by Weijuan Cui (15536306)

“…Thus, we aimed to examine the impact of the co-administration of 17β-estradiol and norethisterone acetate on glycated haemoglobin (HbA1c), fasting glucose, insulin and C-peptide concentrations in females by means of a systematic review and meta-analysis of randomized controlled trials (RCTs).…”

Sold milk, milk composition and feed consumption of cows during BRSV outbreaks in a dairy herd. by Sara Hägglund (580500)

Circulating Tumor Necrosis Factor α Receptors Predict the Outcomes of Human IgA Nephropathy: A Prospective Cohort Study by Yun Jung Oh (165474)

“…The primary clinical endpoint was the decline of estimated glomerular filtration rate (eGFR; ≥ 30% decline compared to baseline). Mean eGFR decreased and proteinuria worsened proportionally as circulating TNFR1 and TNFR2 increased (<i>P</i> < 0.001). …”

FOXJ2 disrupts the binding of CNBP to PGM1 promoter. by Guang-Zhi Jin (2178760)

FOXJ2-up-regulated PGM1 expression inhibits glycolysis, cell proliferation, and HCC development. by Guang-Zhi Jin (2178760)

YFV-Asibi NS4A-5 promotes replication of the cap0 virus. by Anja vom Hemdt (19787189)

Identification of novel pathogenic mutations in <i>ATP6V0A4</i> associated with distal renal tubular acidosis and analysis of wild-type expression in glomerular disease by Yaru Jiang (17458815)

“…Notably, patients with <i>ATP6V0A4</i> mutations were diagnosed at a younger age (mean 0.5 years) and exhibited more severe renal impairment, including reduced estimated glomerular filtration rate (eGFR), indicating heightened susceptibility to kidney damage. …”

PGM1 enhances glycogen synthesis but inhibits aerobic glycolysis. by Guang-Zhi Jin (2178760)

Localization and conditional deletion of C/EBP in SKH1 mouse epidermis. by Kevin J. Mills (9270966)

PGM1 inhibits tumor cell proliferation and tumor growth. by Guang-Zhi Jin (2178760)

Major hyperparameters of RF-SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Pseudo code for coupling model execution process. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Major hyperparameters of RF-MLPR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Results of RF algorithm screening factors. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Degradation of Cell Wall Polysaccharides during Traditional and Tank Fermentation of Chinese Liupao Tea by Xiang Feng (1269054)

“…Traditional fermentation had a greater effect on the cellulose structure, while tank fermentation had a more noticeable impact on HC and WSP.…”