39 research outputs found
Stereochemical plasticity modulates cooperative binding in a CoII12L6 cuboctahedron
Biomolecular receptors are able to process information by responding differentially to combinations of chemical signals. Synthetic receptors that are likewise capable of multi-stimuli response can form the basis of programmable molecular systems, wherein specific input sequences create distinct outputs. Here we report a pseudo-cuboctahedral assembly capable of cooperatively binding anionic and neutral guest species. The binding of pairs of fullerene guests was observed to effect the all-or-nothing cooperative templation of an S6-symmetric host stereoisomer. This bis-fullerene adduct exhibits different cooperativity in binding pairs of anions from the fullerene-free parent: in one case, positive cooperativity is observed, while in another all binding affinities are enhanced by an order of magnitude, and in a third the binding events are only minimally perturbed. This intricate modulation of binding affinity, and thus cooperativity, renders our new cuboctahedral receptor attractive for incorporation into systems with complex, programmable responses to different sets of stimuli.This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC). F.J.R. acknowledges Cambridge Australia Scholarships and the Cambridge Trust for PhD funding
If I stop, then what am I supposed to do? The experiences of sexual intimacy of women who live with provoked vestibulodynia
Excitation energy transfer in partly ordered polymer films differing in donor and acceptor transition moments orientation
Racial and Sex Disparities in Life Expectancy Losses among HIV‐Infected Persons in the United States: Impact of Risk Behavior, Late Initiation, and Early Discontinuation of Antiretroviral Therapy
Short-term electricity demand forecasting based on multiple LSTMs
In recent years, the problem of unbalanced demand and supply in electricity power industry has seriously affected the development of smart grid, especially in the capacity planning, power dispatching and electric power system control. Electricity demand forecasting, as a key solution to the problem, has been widely studied. However, electricity demand is influenced by many factors and nonlinear dependencies, which makes it difficult to forecast accurately. On the other hand, deep neural network technologies are developing rapidly and have been tried in time series forecasting problems. Hence, this paper proposes a novel deep learning model, which is based on the multiple Long Short-Term Memory (LSTM) neural networks to solve the problem of short-term electricity demand forecasting. Compared with autoregressive integrated moving average model (ARIMA) and back propagation neural network (BPNN), our model demonstrates competitive forecast accuracy, which proves that our model is promising for electricity demand forecasting
Dynamic covalent chemistry enables formation of antimicrobial peptide quaternary assemblies in a completely abiotic manner
Pickering stabilized peptide gel particles as tunable microenvironments for biocatalysis
We demonstrate the preparation of peptide gel microparticles that are emulsified and stabilized by SiO2 nanoparticles. The gels are composed of aromatic peptide amphiphiles 9-fluorenylmethoxycarbonyl-diphenylalanine (Fmoc-FF) co-assembled with Fmoc-amino acids with different functional groups (S: serine, D: aspartic acid, K: lysine and Y: tyrosine). The gel-phase provides a highly hydrated matrix and peptide self-assembly endows the matrix with tunable chemical environments which may be exploited to support and stabilize proteins. The use of Pickering emulsion to stabilize these gel particles is advantageous through avoidance of surfactants that may denature proteins. The performance of enzyme lipase B immobilized in pickering/gel microparticles with different chemical functionalities is investigated by studying trans-esterification in heptane. We show that the use of Pickering particles enhances the performance of the enzyme, which is further improved in gel-phase systems, with hydrophilic environment provided by Fmoc-FF/S giving rise to the best catalytic performance. The combination of a tunable chemical environment in gel phase and Pickering stabilization described here is expected to prove useful for areas where proteins are to be exploited in technological contexts such as biocatalysis, also in other areas where protein performance and activity are important, such as biosensors and bioinspired solar fuel devices