(-)-Epigallocatechin-3-gallate encapsulated realgar nanoparticles exhibit enhanced anticancer therapeutic efficacy against acute promyelocytic leukemia by Wei Fang (116739)

“…Compared with nano-realgar and EGCG + RNPs (EGCG and nano-realgar physical mixing), EGCG-RNPs significantly inhibited growth of HL-60 cells. In a solid tumor model, EGCG-RNPs decreased tumor volumes, with an inhibitory rate of 60.18% at a dose of 70 mg · kg⁻¹. …”

Reduction in the spray drift of 2,4-D in tomato using hydraulic nozzles with air induction and LI-700 adjuvant by João de Deus Godinho Júnior (5610011)

“…The treatments were applied in a wind tunnel, under a pressure of 300 kPa. In a laser analyzer, applying only water, the volumetric median diameter, the relative amplitude and the percentage of drops with diameter lower than 150 µm were measured for all nozzle models. …”

Electrical and thermal analyses of catheter-based irreversible electroporation of digestive tract by Fenggang Ren (7020854)

“…All of the NT-IRE protocols were set in BPMs with a voltage of 0.50 kV. With increasing electrode spacing, the minimum pulse number decreased. …”

Abnormal uterine contractions in biglycan/decorin knockout mice. by Zhiping Wu (187917)

Electrocatalytic cogeneration of reactive oxygen species for synergistic water treatment by Yang S.Y.

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Targeted Negative "SEO" Tactics: Facebook by OS BH-Labs (281477)

<b>Metabolic flux analysis revealed </b><b>key roles of </b><b>ArcB</b><b> in ADI pathway and IlvC in BCAA </b><b>biosynthesis </b><b>during </b><b><i>Streptococcus suis</i></b><b>... by Hao Tang (21218903)

Topological properties of the simulated neuronal networks. by Francesca Callegari (14609179)

“…Considering a source neuron labeled in green, it projects connections whose efficacy (size of the colored target neurons) decreases as a function of the distance in according to Eq (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010825#pcbi.1010825.e039" target="_blank">3</a>). …”

AMP-activated protein kinase mediates (-)-epigallocatechin-3-gallate (EGCG) to promote lipid synthesis in mastitis cows by Chunli Hu (11485201)

Macrophage-derived exosomes regulate gastric cancer cell oxaliplatin resistance by wrapping circ 0008253 by Dandan Yu (162326)

Cowpea polyphenol extract regulates galectin gene expression in bovine blood by Sarah Adjei-Fremah (7271633)

Biogenesis of circRBM33 mediated by N6-methyladenosine and its function in abdominal aortic aneurysm by Yingqi Xu (412556)

Expert consensus definition of treatment intolerance in chronic myeloid leukemia in chronic phase by Ehab Atallah (17664292)

Simulation results and their correlation analysis. by Hiroshi Momiji (3254958)

Cause or Effect of Arteriogenesis: Compositional Alterations of Microparticles from CAD Patients Undergoing External Counterpulsation Therapy by Ali Al Kaabi (128670)

“…A total of 1005 proteins were identified by a label-free proteomics approach from MPs of three patients of each group applying stringent acceptance criteria. …”

Functional characterization of GF-TTMn synaptic defects of mutant L1CAM protein expressions in <i>nrg¹⁴</i>;P[nrg180^ΔFIGQY] background. by Sirisha Kudumala (470461)

“…However, in most responding animals that had a decreased ability to follow at a one-to-one ratio at 100 Hz, the Response Latency was increased indicating a reduction in synaptic strength for the GF to TTMn connection.…”

Aspergillus fumigatus G-protein coupled receptors GprM and GprJ are important for the regulation of the cell wall integrity pathway, secondary metabolite production, and virulence by Gustavo Goldman (8849927)

Image 2_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg by Xiuping Xuan (8686266)

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

Data Sheet 1_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

Data Sheet 4_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”