Image 6_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.tif by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

Image 1_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.tif by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

Image 13_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.tif by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

Table 1_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.docx by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

Image 15_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.tif by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

Image 11_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.tif by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

Image 12_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.tif by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

Image 9_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.tif by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

Table 9_Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways.xlsx by Yu Zhang (12946)

“…</p>Results<p>The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. …”

ASP protects the AC16 cells from DOX-induced cardiotoxicity via Nrf2 activation. by Xueyang Bai (20550422)

“…<p>(A) Representative images of protein expression detected by Western blot of p-PI3K,p-AKT, AKT, and the Nrf2 downstream signaling pathways in AC16 cells; (B, C) ML385 does not affect PI3K/AKT (n = 3); (D-F) The statistical results show that ML385 significantly represses NRF2 activation, leading to a decrease in its downstream gene expression (n = 3); (G, H) Lipid ROS levels (n = 3); (I, J) Quantitative q-PCR analysis of relative ANP and BNP mRNA expression (n = 3); (K, L) Representative images (Scale bar =  100 μm) and statistical analysis of JC-1 (n = 150); One-way ANOVA (Tukey post-test), means ±  SD. …”

Study design and plasma viral load. by Zoey K. Wallis (17725175)

Plant Extracellular Nanovesicle-Loaded Hydrogel for Topical Antibacterial Wound Healing <i>In Vivo</i> by Saroj Saroj (13749336)

“…The developed HG was injectable, biocompatible (>95% cell was viable), nonhemolytic (<5% hemolytic capacity), self-healing and exhibited strong physical and mechanical interactions with the bacteria cells (MENV-HG-treated bacteria were significantly more elastic compared to the control in both M. luteus (1.01 ± 0.3 MPa, <i>p</i> < 0.005 vs 5.03 ± 2.6) and E. coli (5.81 ± 2.1 MPa vs 10.81 ± 3.8, <i>p</i> < 0.005). …”

Plant Extracellular Nanovesicle-Loaded Hydrogel for Topical Antibacterial Wound Healing <i>In Vivo</i> by Saroj Saroj (13749336)

“…The developed HG was injectable, biocompatible (>95% cell was viable), nonhemolytic (<5% hemolytic capacity), self-healing and exhibited strong physical and mechanical interactions with the bacteria cells (MENV-HG-treated bacteria were significantly more elastic compared to the control in both M. luteus (1.01 ± 0.3 MPa, <i>p</i> < 0.005 vs 5.03 ± 2.6) and E. coli (5.81 ± 2.1 MPa vs 10.81 ± 3.8, <i>p</i> < 0.005). …”

Example of sample data. by Xiying Wang (4859998)

“…Under a standalone BPNN, the absolute relative error in flow prediction is 1.09%. …”

Structure of BPNN. by Xiying Wang (4859998)

“…Under a standalone BPNN, the absolute relative error in flow prediction is 1.09%. …”

The workflow of EGA-BPNN. by Xiying Wang (4859998)

“…Under a standalone BPNN, the absolute relative error in flow prediction is 1.09%. …”

Algorithm flow of the GA-BPNN model. by Xiying Wang (4859998)

“…Under a standalone BPNN, the absolute relative error in flow prediction is 1.09%. …”

Metric correlation matrix. by Chao Song (379006)

CiLV-C p29 acts as an RNA-binding protein and interacts with eukaryotic initiation factor 4A (eIF4A). by Mikhail Oliveira Leastro (5736329)

Effects of liposomal bupivacaine (LB) and provider experience with LB on service utilization, clinical outcomes, and Medicare expenditures among fee-for-service (FFS) beneficiaries by Sarmistha Pal (13348959)

“…</p> <p>LB use contributed to significant reductions in ED admission (9%; 23.28 vs. 25.69%), STACH admission (8%; 11.61 vs. 12.65%), mortality (39%; 0.67 vs. 1.1%) and opioid prescription fills (6%; 1.8 vs. 1.92) within 180-days post-discharge. …”