Cadaveric cardiosphere-derived cells can maintain regenerative capacity and improve the heart function of cardiomyopathy by Yong Sun (406434)

“…CLH-EDCs were also found to have similar paracrine function in the 24 h group compared to 0 h group. 8 weeks after CM-CDCs transplantion to the injured heart, mean left ventricular ejection fraction increased in both 0 h (64.99 ± 3.4%) and 24 h (62.99 ± 2.8%) CM-CDCs-treated groups as compared to the PBS treated group (53.64 ± 5.6 cm), with a decrease in left ventricular internal diastolic diameter (0.29 ± 0.08 cm and 0.32 ± 0.04 cm in 0 h and 24 h groups, vs. 0.41 ± 0.05 cm in PBS group). …”

Genetic diversity and stock identification of small abalone (<i>Haliotis diversicolor</i>) in Taiwan and Japan by Te-Hua Hsu (3271494)

HDAC1 acts in tandem with T antigen to antagonize the transcriptional activity of CBP by Ester Valls (29650)

“…The data represent an average of at least five independent transfections. A schematic representation of the constructs used is shown at the bottom of the figure. …”

Image1_Identification of miRNAs related to osteoporosis by high-throughput sequencing.jpeg by Jiachun Huang (19350616)

“…The qRT-PCR results showed that miR-140-5p, miR-127-3p, miR-199b-5p, miR-181a-5p, miR-181d-5p, and miR-542-3p exhibited a decrease of 2.27-, 3.00-, 3.48-, 2.67-, 2.41-, and 1.98-fold (all P < 0.05) in osteoporosis compared to controls. …”

Principal dynamic patterns of orthologous genes between worm and fly during embryonic development. by Daifeng Wang (188631)

“…The principal dynamic patterns driven by the worm-specific regulatory network; i.e., worm ePDPs consist of a varied pattern that decreases until the middle stage and then increases (ePDP No.1), an increasing pattern (ePDP No.2), a varied pattern with a peak entering middle stage ((ePDP No.3), a pattern that varies early and then increases during the embryonic development (ePDP No.4), and a cosine-like oscillating pattern with roughly two periods during the embryonic development (ePDP No.5). …”

<b>Characteristic Changes of Gut Microbiome on the Surface of Tissues during the Progression in Colorectal adenoma-carcinoma sequence</b> by 俊成 刘 (17884262)

Synaptic potentiation reduces AP onset, threshold and AHPs. by Sung-Cherl Jung (261358)

“…Examples of APs traces recorded before (black) and 30 min (red) after conditioning stimulation are given for paired and unpaired conditions. Scale bars: 40 mV, 200 ms. (right panel) Pooled data. The threshold to fire the first AP was lowered initially after LTP induction and this decrease persisted throughout the recording episode. …”

Image_3_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.tif by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Table_1_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.xlsx by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Image_9_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.tif by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Image_8_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.tif by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Image_4_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.tif by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Image_6_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.tif by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Table_9_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.xlsx by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Table_3_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.xlsx by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Table_2_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.xlsx by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Image_2_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.tif by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Table_8_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.xls by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Table_7_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.xls by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”

Image_7_Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.tif by Rui Sun (177521)

“…A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. …”