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The androgen receptor (AR) is a target of interest for endocrine disruption research, as altered signaling can affect normal reproductive and neurological development for generations. In an effort to prioritize compounds with alternative methodologies, the U.S. Environmental Protection Agency (EPA) used in vitro data from 11 assays to construct models of AR agonist and antagonist signaling pathways. While these EPA ToxCast AR models require in vitro data to assign a bioactivity score, Bayesian machine learning methods can be used for prospective prediction from molecule structure alone. This approach was applied to multiple types of data corresponding to the EPA's AR signaling pathway with proprietary software, Assay Central. The training performance of all machine learning models, including six other algorithms, was evaluated by internal 5-fold cross-validation statistics. Selleckchem MK571 Bayesian machine learning models were also evaluated with external predictions of reference chemicals to compare prediction accuracies to published results from the EPA. The machine learning model group selected for further studies of endocrine disruption consisted of continuous AC50 data from the February 2019 release of ToxCast/Tox21. These efforts demonstrate how machine learning can be used to predict AR-mediated bioactivity and can also be applied to other targets of endocrine disruption.The SWI/SNF complex is a highly conserved chromatin remodeling complex and can hydrolyze ATP by its catalytic subunit BRG1 or BRM to reconstruct the chromatin. To investigate whether this ATP-dependent chromatin remodeling could affect the DNA conformation, we therefore regulated (knocked down or overexpressed) BRG1/BRM in the cells and applied Fourier transform infrared (FTIR) spectroscopy to probe DNA conformational changes. As a result, we found that BRG1/BRM was indeed associated with the DNA conformational changes, in which knockdown of BRG1/BRM reduced Z-DNA conformation, while overexpression of BRG1/BRM enhanced Z-DNA conformation. This Z-DNA conformational transformation was also verified using the Z-DNA-binding proteins. Therefore, this work has provided a direct analytical tool to probe Z-DNA transformation upon ATP-dependent chromatin remodeling.Cis-prenyltransferases such as undecaprenyl diphosphate synthase (UPPS) and decaprenyl diphosphate synthase (DPPS) are essential enzymes in bacteria and are involved in cell wall biosynthesis. UPPS and DPPS are absent in the human genome, so they are of interest as targets for antibiotic development. Here, we screened a library of 750 compounds from National Cancer Institute Diversity Set V for the inhibition of Mycobacterium tuberculosis DPPS and found 17 hits, and then IC50s were determined using dose-response curves. Compounds were tested for growth inhibition against a panel of bacteria, for in vivo activity in a Staphylococcus aureus/Caenorhabditis elegans model, and for mammalian cell toxicity. The most active DPPS inhibitor was the dicarboxylic acid redoxal (compound 10), which also inhibited undecaprenyl diphosphate synthase (UPPS) as well as farnesyl diphosphate synthase. 10 was active against S. aureus, Clostridiodes difficile, Bacillus anthracis Sterne, and Bacillus subtilis, and there was a 3.4-fold increase in IC50 on addition of a rescue agent, undecaprenyl monophosphate. We found that 10 was also a weak protonophore uncoupler, leading to the idea that it targets both isoprenoid biosynthesis and the proton motive force. In an S. aureus/C. elegans in vivo model, 10 reduced the S. aureus burden 3 times more effectively than did ampicillin.Here we report two highly emissive perylene diimide (PDI)-based metallacages and explore their complexation with polycyclic aromatic hydrocarbons, such as pyrene, triphenylene, and perylene. The fluorescence quantum yields of metallacages exceed 90% and their binding constants with perylene can reach as high as 2.41 × 104 M-1 in acetonitrile. These features enable further tuning of the emission of the host-guest complexes to obtain white-light emission based on the complementary orange emission of the metallacages and the blue emission of perylene. Moreover, owing to the huge differences of their quantum yields in solution and in the solid state, the host-guest complexes are successfully employed for information encryption. This study offers a general approach for the construction of emissive metallacages and explores their application for information encryption.Herein, aggregation-induced electrochemiluminescence (AIECL) of tetraphenylbenzosilole derivatives in an aqueous phase system with the participation of a co-reactant was systematically investigated for the first time. All organics that we studied exhibit excellent stability and dramatically enhanced electrochemiluminescence (ECL) and photoluminescence (PL) emission when the water fraction increases. The influence of substituents in the structure of tetraphenylbenzosilole derivatives on AIECL performance was proved by fluorescence, cyclic voltammetry, and related theoretical calculation. Among them, 2,3-bis(4-cyanophenyl)-1,1-diphenyl-benzosilole (TPBS-C) with strong electron-withdrawing cyano groups exhibits the best ECL behavior with the highest ECL efficiency (184.36%). The strongest ECL emission of TPBS-C not only stems from the aggregated molecules that restrict the intramolecular motion of peripheral phenyl groups, which inhibits the nonradiative transition, but also comes from the fact that TPBS-C has the lowest reduction potential, and twice the reduction process of TPBS-C occurs to produce more anion radicals (TPBS-C·-). Significantly, the ECL sensor based on TPBS-C nanoaggregates exhibits excellent detection performance for toxic Cr(VI) with a wide linear range from 10-12 to 10-4 M and an extremely low detection limit of 0.83 pM. This work developed an efficient luminophore with unique AIECL properties and realized the ultrasensitive detection of Cr(VI) in the aqueous phase system.Typical organic photovoltaic materials show high Urbach energies (ca. 25-50 meV), which is considerably higher than those of their inorganic counterparts and limits further improvement in the device efficiency of organic solar cells (OSCs). In this study, we introduce a facile method of selenium substitution to reduce the Urbach energy of organic photovoltaic materials to 20.4 meV (Y6Se), which is the lowest value reported for high-performance organic photovoltaic materials and very close to those (ca. 15 meV) of typical inorganic/hybrid semiconductors, such as crystalline silicon, gallium nitride, and lead-halide perovskite. Next, OSCs based on Y6Se showed 17.7% efficiency, which is among the best results for OSCs and the record efficiency of as-cast single junction OSCs to date.
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