Improving the robustness of maritime emission inventories is important to ensure we fully understand the point of embarkment for transformation pathways of the sector toward the 1.5 and 2°C targets. A bottom-up assessment of emissions of greenhouse gases and aerosols from the maritime sector is presented, accounting for the emissions from fuel production and processing, resulting in a complete “well-to-wake” geospatial inventory. This high-resolution inventory is developed through the use of the state-of-the-art data-driven MariTEAM model, which combines ship technical specifications, ship location data, and historical weather data. The CO2 emissions for 2017 amount to 943 million tonnes, which is 11% lower than the fourth International Maritime Organization’s greenhouse gas study for the same year, while larger discrepancies have been found across ship segments. If fuel production is accounted for when developing shipping inventories, total CO2 emissions reported could increase by 11%. In addition to fuel production, effects of weather and heavy traffic regions were found to significantly impact emissions at global and regional levels. The global annual efficiency for different fuels and ship segments in approximated operational conditions were also investigated, indicating the need for more holistic metrics than current ones when seeking appropriate solutions aiming at reducing emissions.Black spot disease caused by Ceratocystis fimbriata is destructive to the production, transportation, and storage of sweet potato. The antifungal effects of Bacillus tequilensis XK29 against C. fimbriata through volatile organic compounds (VOCs) were evaluated in this study. The activated carbon assay proved that XK29 could exert antibiotic effects through volatiles. By optimizing the wheat seed weight, inoculation method, concentration, volume, and time, the antifungal activity of XK29 was significantly improved. XK29 fumigation inhibited spore formation and germination and changed the cell morphology of C. fimbriata. During the storage of sweet potato tuber roots, XK29 effectively controlled black spot disease and reduced the weight loss and malondialdehyde content. Metabolomic analysis revealed that 21 volatile compounds were released from XK29. Isovaleric acid, isobutyric acid, and 2-methylbutanoic acid effectively inhibited the growth of C. fimbriata. These results indicate that B. tequilensis XK29 has a good potential to be developed as a microbial fumigation agent.Acyl glucuronides are common metabolites of carboxylic acid-containing compounds. Since acyl glucuronides sometimes show high reactivity, they are considered to be involved in drug toxicity. Therefore, it is important to evaluate the risk posed by acyl glucuronides in the development of safe drugs; however, there are no suitable evaluation methods for the early stages of drug discovery. We aimed to develop a trapping reagent that detects reactive acyl glucuronides to assess their risk. We designed a diamine-structured trapping reagent, Dap-Dan, and compared its trapping ability with the reported one that has an amino group, and results showed that Dap-Dan showed higher accuracy. In the trapping assay with 17 medicines containing a carboxylic acid, Dap-Dan trapped acyl glucuronides that had a higher risk of toxicity. In conclusion, Dap-Dan can be useful for evaluating the risk of reactive acyl glucuronides.We report on the synthesis and structural characterization of a giant, discrete, and neutral molecular disk, [Pd40O24(OH)16(CH3)2AsO216] (Pd40), comprising a 40-palladium-oxo core that is capped by 16 dimethylarsinate moieties, resulting in a palladium-oxo cluster (POC) with a diameter of ∼2 nm. Pd40, which is the largest known neutral Pd-based oxo cluster, can be isolated either as a discrete species or constituting a 3D H-bonded organic-inorganic framework (HOIF) with a 12-tungstate Keggin ion, [SiW12O40]4- or [GeW12O40]4-. 1H and 13C NMR as well as 1H-DOSY NMR studies indicate that Pd40 is stable in aqueous solution, which is also confirmed by ESI-MS studies. Pd40 was also immobilized on a mesoporous support (SBA15) followed by the generation of size-controlled Pd nanoparticles (diameter ∼2-6 nm, as based on HR-TEM), leading to an effective heterogeneous hydrogenation catalyst for the transformation of various arenes to saturated carbocycles.In this paper, an enzymatic route for synthesizing phenolic glycoside azelaic acid esters was successfully set up via lipase-catalyzed esterification and transesterification. Among the lipases tested, Candida antarctica lipase B (Novozyme 435) showed the highest activity in catalyzing esterification and Thermomyces lanuginosus (Lipozyme TLIM) gave the highest substrate conversion in catalyzing transesterification for the synthesis of ester. The addition of 4A molecular sieves into the reaction system is found to be an effective method for in situ absorption of the byproduct water and methanol, with which the substrate conversions of the enzymatic esterification and transesterification were 98.7 and 95.1%, respectively. Also, the main product ratios in transesterification were above 99.0% with lipozyme TLIM as a catalyst because the hydrolysis reaction was hindered. The results of the physical and biological properties indicate that all esters had higher Clog p values than their parent compounds. Also, the esters showed higher intracellular tyrosinase inhibitory and depigmentating activities than phenolic glycosides, azelaic acid (AA), and their physical mixtures due to their higher membrane penetration and tyrosinase inhibitory effects. In particular, piceid 6″-O-azelaic acid ester (PIA) showed the strongest inhibitory effect against melanin production. Its inhibitory rate was 77.4% at a concentration of 0.25 mM, about 4.2 times higher than that of arbutin (18.5%).The NRF2-mediated cytoprotective response is central to cellular homoeostasis, and there is increasing interest in developing small-molecule activators of this pathway as therapeutics for diseases involving chronic oxidative stress. The protein KEAP1, which regulates NRF2, is a key point for pharmacological intervention, and we recently described the use of fragment-based drug discovery to develop a tool compound that directly disrupts the protein-protein interaction between NRF2 and KEAP1. We now present the identification of a second, chemically distinct series of KEAP1 inhibitors, which provided an alternative chemotype for lead optimization. Pharmacophoric information from our original fragment screen was used to identify new hit matter through database searching and to evolve this into a new lead with high target affinity and cell-based activity. We highlight how knowledge obtained from fragment-based approaches can be used to focus additional screening campaigns in order to de-risk projects through the rapid identification of novel chemical series.Quantum machine-learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure calculations of molecular systems and spin models in magnetic systems. However, the discussion in all these recipes focuses specifically on targeting the ground state. Herein we demonstrate a quantum algorithm that can filter any energy eigenstate of the system based on either symmetry properties or a predefined choice of the user. see more The workhorse of our technique is a shallow neural network encoding the desired state of the system with the amplitude computed by sampling the Gibbs-Boltzmann distribution using a quantum circuit and the phase information obtained classically from the nonlinear activation of a separate set of neurons. We show that the resource requirements of our algorithm are strictly quadratic. To demonstrate its efficacy, we use state filtration in monolayer transition metal dichalcogenides which are hitherto unexplored in any flavor of quantum simulations. We implement our algorithm not only on quantum simulators but also on actual IBM-Q quantum devices and show good agreement with the results procured from conventional electronic structure calculations. We thus expect our protocol to provide a new alternative in exploring the band structures of exquisite materials to usual electronic structure methods or machine-learning techniques that are implementable solely on a classical computer.Physiologically based pharmacokinetic (PBPK) modeling is a powerful technique to inform risk assessment of xenobiotic substances such as perfluorooctanoic acid (PFOA). In our previous study, a permeability-limited PBPK model was developed to simulate the toxicokinetics and tissue distribution of PFOA in male rats. However, due to limited information on some key model parameters (e.g., protein binding and active transport rates), the uncertainty of the permeability-limited PBPK model was quite high. To address this issue, a hierarchical Bayesian analysis with Markov chain Monte Carlo (MCMC) was applied to reduce the uncertainty of parameters and improve the performance of the PBPK model. With the optimized posterior parameters, the PBPK model was evaluated by comparing its prediction with experimental data from three different studies. The results show that the uncertainties of the posterior model parameters were reduced substantially. In addition, most of the PBPK model predictions were improved with the posterior parameters, most of the predicted plasma toxicokinetics (e.g., half-life) and tissue distribution fell well within a factor of 2.0 of the experimental data. Finally, the Bayesian framework could provide insights into the molecular mechanisms driving PFOA toxicokinetics PFOA-protein binding, membrane permeability, and active transport.Unlike counterion interactions with charged interfaces, the influence of co-ions is only scarcely reported in the literature. In this work, the effect of SCN- and the halide co-ions in the interactions of Na+ with carboxylic acid Langmuir monolayers is investigated by using vibrational sum frequency spectroscopy. At 1 M concentrations in the subphase, the identity of the anion is shown to have a remarkable influence on the charging behavior and degree of deprotonation of the monolayer, with ions ordering in the sequence I- > SCN- > Cl- ≈ Br-. The same trend is observed at both pH 6 and pH 9 when the monolayer is intrinsically more charged. Spectroscopic evidence is found for both the presence of I- and SCN- in the interfacial region at levels close to their detection limits. The results contradict electrostatic theories on charged interfaces where co-ions are not expected to play any significant role. The higher propensity for the large polarizable anions to deprotonate the monolayer is explained in terms of their ability to modify the cations affinity toward the carboxylic acid groups present at the surface.There is growing evidence from human and animal studies indicating an association between exposure to synthetic food dyes and adverse neurobehavioral outcomes in children. However, data gaps persist for potential mechanisms by which the synthetic food dyes could elicit neurobehavioral impacts. We developed an approach to evaluate seven US FDA-batch-certified food dyes using publicly available high-throughput screening (HTS) data from the US EPA’s Toxicity Forecaster to assess potential underlying molecular mechanisms that may be linked to neurological pathway perturbations. The dyes were screened through 270 assays identified based on whether they had a neurological-related gene target and/or were mapped to neurodevelopmental processes or neurobehavioral outcomes, and were conducted in brain tissue, targeted specific hormone receptors, or targeted oxidative stress and inflammation. Some results provided support for neurological impacts found in human and animal studies, while other results showed a lack of correlation with in vivo findings.