Comparison of the decrease of CFU in CSF and blood between treatment groups within the first 6 h after treatment. by Luca G. Valente (12463057)

Three-dimensional (3D) Collagen Type I gel formula (5 mg/mL). by Melissa A. MacIver (12850566)

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Respective increase and decrease in Myc and NRF1/TFAM in kidneys from rats administered Tl. by Sho Sugahara (11895828)

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<i>Aspergillus flavus</i> mRNA expression (a) <i>aflD</i> and (c) <i>aflR</i> and phylogenetic analysis of (b) <i>aflD</i> and (d) <i>aflR</i> after exposure to 50 mg/mL of <i>U. e... by Martha Cebile Jobe (21175426)

The catalase enzyme response of <i>A</i>. <i>albopictus</i> larvae decreased (1.5-fold) in response to <i>M</i>. <i>robertsii</i>-derived copper nanoparticles. by Perumal Vivekanandhan (4863484)

This is the raw data of Immunofluorescence in Met-5A cell. by Yangyang Yin (14323701)

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Combination treatment induced more cell death and decreased cell survival markers more than did single treatments. by Panchanan Maiti (1459852)

MVK activates microglia and decreases phagocytosis. by Ren Y. Sato (16914027)

This is the raw data of Western blot in Met-5A cell. by Yangyang Yin (14323701)

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Testis tissue apoptosis post PM2.5 exposure. by Cao Wang (1500691)

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Combination treatment decreased PI3K/Akt/mTOR pathways more efficiently than SLCP or BBR treatments alone. by Panchanan Maiti (1459852)

Tax expression is associated with decreased cellular motility. by Saumya Ramanayake (7879091)

Metformin pre-treatment retains an antioxidant effect and decreases apoptosis, in an AMPK activation manner. by Silvia Siteni (10344070)

Fig 5 - by Saeed El-Ashram (710370)

Fig 5 - by Wenping Dong (3854437)

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Effects of H5 (20 and 40 mg/kg, p.o.), and diazepam (2.5 mg/kg, i.p.) in the Rota-rod test in mice. by Maria Alice Miranda Bezerra Medeiros (11752002)

Primary pharmacokinetic parameters of paclitaxel in rats after intravenous administration of Taxol, Abraxane, or self-made nanoparticles at a paclitaxel dose of 7mg/kg (<i>n</i> =... by Yue Gao (263086)

Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 12 covariates chosen using subjective feature selection. by Dennis Ochola (11626912)

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Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 17 covariates selected after recursive feature selection. by Dennis Ochola (11626912)

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Fig 5 - by Te-Hsing Hsu (16973374)