Neither 9-cisRA nor atRA inhibit TGF-β1 induced activation of the Smad3-dependent reporter gene, SBE12-lux.

<p>SBE12-lux activity was normalized to treatment with 50 pM TGF-β1 set to 100%. TGF-β1-induced luciferase activity was inhibited by 1 µM SB431542. atRA and 9-cisRA did not inhibit TGF-β1 activation of SBE-lux.</p

C2C12 muscle differentiation is inhibited by TGF-β1 and restored by 9-cisRA or atRA.

<p>Vehicle control had no effect on C2C12 differentiation or cell proliferation (A and E) (scale bar = 100 µm). TGF-β1 inhibited C2C12 myotube formation and increased cell number (B and F). 9-cisRA (500 nM) or atRA (250 nM) restored differentiation of C2C12 cells (C and D) and reduced cell number (G and H) in the presence of TGF-β1.</p

Compounds tested for their ability to overcome the anti-myogenic effect of TGF-β1 in C2C12 cells.

<p>Compounds tested for their ability to overcome the anti-myogenic effect of TGF-β1 in C2C12 cells.</p

Vitamin D prevents retinoic acid mediated rescue of differentiation in TGF-β1 treated C2C12 cells.

<p>C2C12 cells were treated with 50 pM TGF-β1 and either 500 nM 9-cisRA (A) or 250 nM atRA (B) and increasing concentrations of vitamin D for 96 hours. Increasing concentrations of vitamin D reduced the percent of MHC positive nuclei, i.e. myoblast differentiation, with an IC50 of 30 pM in the presence of 9-cisRA (A) or 39 pM in the presence of atRA (B).</p

Dose-Response of SB431542 on C2C12 proliferation and differentiation in the presence of TGF-β1.

<p>TGF-β1 (50 pM) was used to inhibit C2C12 differentiation. (A) Increasing concentrations of SB431542 caused a decrease in the number of nuclei with an IC50 of 323 nM. (B) SB431542 overcame the TGF-β1 inhibition of C2C12 differentiation with an EC50 of 166 nM. At 10 µM SB431542, we observed a slight but reproducible reduction in the percent of MHC positive nuclei.</p

Dose-Response of TGF-β1 on C2C12 Proliferation and Differentiation.

<p>C2C12 cells were treated with different concentrations of TGF-β1 for 96 hours and stained for nuclei and MHC. (A) Cell proliferation, as denoted by number of nuclei, increased in a dose-dependent manner with an EC50 for TGF-β1 of 17 pM. (B) Myoblast differentiation, as measured by percentage of nuclei positive for MHC, decreased with increasing concentrations of TGF-β1 with an IC50 of 23 pM.</p

Thalassosamide, a Siderophore Discovered from the Marine-Derived Bacterium <i>Thalassospira profundimaris</i>

Here we describe the rapid identification and prioritization of novel active marine natural products using an improved dereplication strategy. During the course of our screening of marine natural product libraries, a new cyclic trihydroxamate compound, thalassosamide, was discovered from the α-proteobacterium <i>Thalassospira profundimaris</i>. Its structure was determined by 2D NMR and MS/MS experiments, and the absolute configuration of the lysine-derived units was established by Marfey’s analysis, whereas that of C-9, 9′, and 9″ was determined via the circular dichroism data of the [Rh₂(OCOCF₃)₄] complex and DFT NMR calculations. Thalassosamide showed moderate in vivo efficacy against <i>Pseudomonas aeruginosa</i>

Machine Learning Consensus Scoring Improves Performance Across Targets in Structure-Based Virtual Screening

In structure-based virtual screening, compound ranking through a consensus of scores from a variety of docking programs or scoring functions, rather than ranking by scores from a single program, provides better predictive performance and reduces target performance variability. Here we compare traditional consensus scoring methods with a novel, unsupervised gradient boosting approach. We also observed increased score variation among active ligands and developed a statistical mixture model consensus score based on combining score means and variances. To evaluate performance, we used the common performance metrics ROCAUC and EF1 on 21 benchmark targets from DUD-E. Traditional consensus methods, such as taking the mean of quantile normalized docking scores, outperformed individual docking methods and are more robust to target variation. The mixture model and gradient boosting provided further improvements over the traditional consensus methods. These methods are readily applicable to new targets in academic research and overcome the potentially poor performance of using a single docking method on a new target

Dose-responses of HuAoSMCs and HuAoECs to idarubicin treatment.

<p>Proliferation of SMCs or ECs in the presence of various concentrations of idarubicin or resveratrol was assayed in a 96-well plate and handled by the same robotic system as described in Materials and Methods. Each data point is a mean ± SD of triplicates, *P<0.05.</p

Test of reproducibility of the automated 96-well proliferation assay format.

<p>Experiments were performed as described in detail in Materials and Methods. DMSO (40 wells) and resveratrol (40 wells) were used as negative control and positive control, respectively. Data are presented either as Alamar Blue fluorescence reading from individual wells (A), or a mean ± SD (standard deviation) of 40 wells (B) (***P<0.001).</p