Pereira Carr (sneezebengal9)

Diagnostic ion-molecule reactions employed in tandem mass spectrometry experiments can frequently be used to differentiate between isomeric compounds unlike the popular collision-activated dissociation methodology. Selected neutral reagents, such as 2-methoxypropene (MOP), are introduced into an ion trap mass spectrometer where they react with protonated analytes to yield product ions that are diagnostic for the functional groups present in the analytes. However, the understanding and interpretation of the mass spectra obtained can be challenging and time-consuming. Here, we introduce the first bootstrapped decision tree model trained on 36 known ion-molecule reactions with MOP. It uses the graph-based connectivity of analytes' functional groups as input to predict whether the protonated analyte will undergo a diagnostic reaction with MOP. A Cohen kappa statistic of 0.70 was achieved with a blind test set, suggesting substantial inter-model reliability on limited training data. Prospective diagnostic product predictions were experimentally tested for 13 previously unpublished analytes. We introduce chemical reactivity flowcharts to facilitate chemical interpretation of the decisions made by the machine learning method that will be useful to understand and interpret the mass spectra for chemical reactivity.Anions generally associate more favorably with the air-water interface than cations. In addition to solute size and polarizability, the intrinsic structure of the unperturbed interface has been discussed as an important contributor to this bias. Here we assess quantitatively the role that intrinsic charge asymmetry of water's surface plays in ion adsorption, using computer simulations to compare model solutes of various size and charge. In doing so, we also evaluate the degree to which linear response theory for solvent polarization is a reasonable approach for comparing the thermodynamics of bulk and interfacial ion solvation. Consistent with previous works on bulk ion solvation, we find that the average electrostatic potential at the center of a neutral, sub-nanometer solute at the air-water interface depends sensitively on its radius, and that this potential changes quite nonlinearly as the solute's charge is introduced. The nonlinear response closely resembles that of the bulk. As a result, the net nonlinearity of ion adsorption is weaker than in bulk, but still substantial, comparable to the apparent magnitude of macroscopically nonlocal contributions from the undisturbed interface. For the simple-point-charge model of water we study, these results argue distinctly against rationalizing ion adsorption in terms of surface potentials inherent to molecular structure of the liquid's boundary.Oligonucleotide-templated reactions are frequently exploited for target detection in biosensors and for the construction of DNA-based materials and probes in nanotechnology. However, the translation of the specifically used template chemistry from solution to surfaces, with the final aim of achieving highly selective high-throughput systems, has been difficult to reach and therefore, poorly explored. Here, we show the first example of a visible light-triggered templated ligation on a surface, employing furan-modified peptide nucleic acids (PNAs). Tailored photo-oxidation of the pro-reactive furan moiety is ensured by the simultaneous introduction of a weak photosensitizer as well as a nucleophilic moiety in the reacting PNA strand. This allows one to ensure a localized production of singlet oxygen for furan activation, which is not affected by probe dilution or reducing conditions. Simple white light irradiation in combination with target-induced proximity between reactive functionalities upon recognition of a short 22mer DNA or RNA sequence that functions as a template, allows sensitive detection of nucleic acid targets in a 96 well plate format.The NLRP3 inflammasome regulates production of the pro-inflammatory cytokines interleukin-