The accurate detection of biological materials has remained at the forefront of scientific research for decades. This includes the detection of molecules, proteins, and bacteria. Biomimetic sensors look to replicate the sensitive and selective mechanisms that are found in biological systems and incorporate these properties into functional sensing platforms. Molecularly imprinted polymers (MIPs) are synthetic receptors that can form high affinity binding sites complementary to the specific analyte of interest. They utilise the shape, size, and functionality to produce sensitive and selective recognition of target analytes. One route of synthesizing MIPs is through electropolymerization, utilising predominantly constant potential methods or cyclic voltammetry. This methodology allows for the formation of a polymer directly onto the surface of a transducer. The thickness, morphology, and topography of the films can be manipulated specifically for each template. Recently, numerous reviews have been published in the production and sensing applications of MIPs; however, there are few reports on the use of electrosynthesized MIPs (eMIPs). The number of publications and citations utilising eMIPs is increasing each year, with a review produced on the topic in 2012. This review will primarily focus on advancements from 2012 in the use of eMIPs in sensing platforms for the detection of biologically relevant materials, including the development of increased polymer layer dimensions for whole bacteria detection and the use of mixed monomer compositions to increase selectivity toward analytes.

We use a recently developed coarse-grained model for DNA to study kissing complexes formed by hybridization of complementary hairpin loops. The binding of the loops is topologically constrained because their linking number must remain constant. By studying systems with linking numbers −1, 0, or 1 we show that the average number of interstrand base pairs is larger when the topology is more favourable for the right-handed wrapping of strands around each other. The thermodynamic stability of the kissing complex also decreases when the linking number changes from −1 to 0 to 1. The structures of the kissing complexes typically involve two intermolecular helices that coaxially stack with the hairpin stems at a parallel four-way junction.

Modern theories of the hydrophobic effect highlight its dependence on length scale, emphasizing the importance of interfaces in the vicinity of sizable hydrophobes. We recently showed that a faithful treatment of such nanoscale interfaces requires careful attention to the statistics of capillary waves, with significant quantitative implications for the calculation of solvation thermodynamics. Here, we show that a coarse-grained lattice model like that of Chandler [Chandler D (2005) Nature 437(7059):640-647], when informed by this understanding, can capture a broad range of hydrophobic behaviors with striking accuracy. Specifically, we calculate probability distributions for microscopic density fluctuations that agree very well with results of atomistic simulations, even many SDs from the mean and even for probe volumes in highly heterogeneous environments. This accuracy is achieved without adjustment of free parameters, because the model is fully specified by well-known properties of liquid water. As examples of its utility, we compute the free-energy profile for a solute crossing the air-water interface, as well as the thermodynamic cost of evacuating the space between extended nanoscale surfaces. These calculations suggest that a highly reduced model for aqueous solvation can enable efficient multiscale modeling of spatial organization driven by hydrophobic and interfacial forces.hydrophobic effect | self-assembly | coarse-grained model | lattice models H ydrophobic forces play a crucial role in biological self-assembly, protein folding, ion channel gating, and lipid membrane dynamics (1-9). The origin and strength of these forces are well understood at extreme length scales, based on the recognition that accommodating an ideal volume-excluding hydrophobe in water carries the same thermodynamic cost as evacuating solvent from the corresponding volume. On the scale of a small molecule like methane, density fluctuations that enable such evacuation are Gaussian-distributed to a very good approximation, even far from the mean (10). Linear response theories, such as Pratt-Chandler theory, can thus be quite accurate for assessing solvation of individual small hydrophobic species.Solvation at much larger scales is, by contrast, dominated by water's proximity to liquid-vapor coexistence. Hydrophobic forces involving extended substrates are shaped by the physics of interfaces and are quantified by macroscopic parameters like surface tension. In between these extremes, a rich variety of hydrophobic effects results from the combined importance of nearby phase coexistence and details of intermolecular structure. Capturing this interplay, for instance, near a biological macromolecule, presents a significant challenge for theory.Lum-Chandler-Weeks (LCW) theory represents the modern understanding of hydrophobic solvation, providing a conceptual and mathematical framework to couple interfacial forces with the short-wavelength density fluctuations that determine solvation of small molecules (10, 11). The theory's physical pers...

Molecularly Imprinted Polymers (MIPs) were synthesised for the selective detection of amoxicillin in aqueous samples. Different functional monomers were tested to determine the optimal composition via batch rebinding experiments. Two different sensor platforms were tested using the same MIP solution; one being bulk synthesized and surface modified Screen Printed Electrodes (SPEs) via drop casting the microparticles onto the electrode surface and the other being UV polymerized directly onto the SPE surface in the form of a thin film. The sensors were used to measure amoxicillin in conjunction with the Heat-Transfer Method (HTM), a low-cost and simple thermal detection method that is based on differences in the thermal resistance at the solid–liquid interface. It was demonstrated that both sensor platforms could detect amoxicillin in the relevant concentration range with Limits of Detection (LOD) of 1.89 ± 1.03 nM and 0.54 ± 0.10 nM for the drop cast and direct polymerisation methods respectively. The sensor platform utilising direct UV polymerisation exhibited an enhanced response for amoxicillin detection, a reduced sensor preparation time and the selectivity of the platform was proven through the addition of nafcillin, a pharmacophore of similar shape and size. The use of MIP-modified SPEs combined with thermal detection provides sensors that can be used for fast and low-cost detection of analytes on-site, which holds great potential for contaminants in environmental aqueous samples. The platform and synthesis methods are generic and by adapting the MIP layer it is possible to expand this sensor platform to a variety of relevant targets.

Near-infrared spectroscopy monitoring provides a practical method to follow trends in superficial cerebral cortex oxygenation during and after cardiovascular surgery. Determination of the limits of cerebral pressure–flow autoregulation is now possible using processed oximetry signals in relation to arterial pressure.

A Bayesian formulation for a popular conjunctive cognitive diagnosis model, the reduced reparameterized unified model (rRUM), is developed. The new Bayesian formulation of the rRUM employs a latent response data augmentation strategy that yields tractable full conditional distributions. A Gibbs sampling algorithm is described to approximate the posterior distribution of the rRUM parameters. A Monte Carlo study supports accurate parameter recovery and provides evidence that the Gibbs sampler tended to converge in fewer iterations and had a larger effective sample size than a commonly employed Metropolis–Hastings algorithm. The developed method is disseminated for applied researchers as an R package titled “rRUM.”

Antidepressants such as amitryptiline and fluoxetine are on the list of modern essential medicines of the World Health Organization. However, there are growing concerns regarding the ecological impact of these pharmaceuticals, leading to a great need to improve current wastewater treatment procedures. In this contribution, we will report on the use of molecularly imprinted polymers (MIPs) for the extraction of antidepressants in water samples. MIPs were developed for fluoxetine and duloxetine, antidepressants belonging to the class of selective serotonin reuptake inhibitors (SSRIs). The binding capacity of these microparticles was evaluated using ultraviolet–visible (UV–Vis) spectroscopy. A new high-performance liquid chromatography (HPLC) procedure coupled to UV detection was developed, which enabled the study of mixtures of fluoxetine and duloxetine with other nitrogen-containing compounds. These results indicate that it is possible to selectively extract SSRIs from complex samples. Therefore, these versatile polymers are a promising analytical tool for the clean-up of water samples, which will benefit aquatic life and reduce the ecological impact of pharmaceuticals.

In this communication, molecularly imprinted nanoparticles (nanoMIPs) that are produced by solid-phase synthesis are functionalised onto thermistors via dip-coating.