Electroweak radiative corrections to muon capture

Electroweak radiative corrections to muon capture on nuclei are computed and found to be sizable. They enhance the capture rates for hydrogen and helium by 2.8% and 3.0%, respectively. As a result, the value of the induced pseudoscalar coupling, g(P)(exp), extracted from a recent hydrogen 1S singlet capture experiment is increased by about 21% to g(P)(exp)=7.3+/-1.2 and brought into good agreement with the prediction of chiral perturbation theory, g(P)(theory)=8.2+/-0.2. Implications for helium capture rate predictions are also discussed.     

Organozinc Pivalate Reagents: Segregation,Solubility, Stabilization,and Structural Insights

The pivalates RZnOPiv?Mg(OPiv)X?n LiCl (OPiv=pivalate; R=aryl; X=Cl, Br, I) stand out amongst salt‐supported organometallic reagents, because apart from their effectiveness in Negishi cross‐coupling reactions, they show more resistance to attack by moist air than conventional organometallic compounds. Herein a combination of synthesis, coupling applications, X‐ray crystallographic studies, NMR (including DOSY) studies, and ESI mass spectrometric studies provide details of these pivalate reagents in their own right. A p‐tolyl case system shows that in [D₈]THF solution these reagents exist as separated Me(p‐C₆H₄)ZnCl and Mg(OPiv)₂ species. Air exposure tests and X‐ray crystallographic studies indicate that Mg(OPiv)₂ enhances the air stability of aryl zinc species by sequestering H₂O contaminants. Coupling reactions of Me(p‐C₆H₄)ZnX (where X=different salts) with 4‐bromoanisole highlight the importance of the presence of Mg(OPiv)₂. Insight into the role of LiCl in these multicomponent mixtures is provided by the molecular structure of [(THF)₂Li₂(Cl)₂(OPiv)₂Zn].     

On the strength of hydrogen bonding within water clusters on the coordination limit

Hydrogen bonds (HB) are arguably the most important noncovalent interactions in chemistry. We study herein how differences in connectivity alter the strength of HBs within water clusters of different sizes. We used for this purpose the interacting quantum atoms energy partition, which allows for the quantification of HB formation energies within a molecular cluster. We could expand our previously reported hierarchy of HB strength in these systems (Phys. Chem. Chem. Phys., 2016, 18 , 19557) to include tetracoordinated monomers. Surprisingly, the HBs between tetracoordinated water molecules are not the strongest HBs despite the widespread occurrence of these motifs (e.g., in ice I_h). The strongest HBs within H₂O clusters involve tricoordinated monomers. Nonetheless, HB tetracoordination is preferred in large water clusters because (a) it reduces HB anticooperativity associated with double HB donors and acceptors and (b) it results in a larger number of favorable interactions in the system. Finally, we also discuss (a) the importance of exchange-correlation to discriminate among the different examined types of HBs within H₂O clusters, (b) the use of the above-mentioned scale to quickly assess the relative stability of different isomers of a given water cluster, and (c) how the findings of this research can be exploited to indagate about the formation of polymorphs in crystallography. Overall, we expect that this investigation will provide valuable insights into the subtle interplay of tri- and tetracoordination in HB donors and acceptors as well as the ensuing interaction energies within H₂O clusters.     

Semiconductor Quantum Dots as Components of Photoactive Supramolecular Architectures

Luminescent quantum dots (QDs) are colloidal semiconductor nanocrystals consisting of an inorganic core covered by a molecular layer of organic surfactants. Although QDs have been known for more than thirty years, they are still attracting the interest of researchers because of their unique size-tunable optical and electrical properties arising from quantum confinement. Moreover, the controlled decoration of the QD surface with suitable molecular species enables the rational design of inorganic-organic multicomponent architectures that can show a vast array of functionalities. This minireview highlights the recent progress in the use of surface-modified QDs – in particular, those based on cadmium chalcogenides – as supramolecular platforms for light-related applications such as optical sensing, triplet photosensitization, photocatalysis and phototherapy.     

Iboga Inspired N-Indolylethyl-Substituted Isoquinuclidines as a Bioactive Scaffold: Chemoenzymatic Synthesis and Characterization as GDNF Releasers and Antitrypanosoma Agents

The first stage of the drug discovery process involves the identification of small compounds with biological activity. Iboga alkaloids are monoterpene indole alkaloids (MIAs) containing a fused isoquinuclidine-tetrahydroazepine ring. Both the natural products and the iboga-inspired synthetic analogs have shown a wide variety of biological activities. Herein, we describe the chemoenzymatic preparation of a small library of novel N-indolylethyl-substituted isoquinuclidines as iboga-inspired compounds, using toluene as a starting material and an imine Diels–Alder reaction as the key step in the synthesis. The new iboga series was investigated for its potential to promote the release of glial cell line-derived neurotrophic factor (GDNF) by C6 glioma cells, and to inhibit the growth of infective trypanosomes. GDNF is a neurotrophic factor widely recognized by its crucial role in development, survival, maintenance, and protection of dopaminergic neuronal circuitries affected in several neurological and psychiatric pathologies. Four compounds of the series showed promising activity as GDNF releasers, and a leading structure (compound 11) was identified for further studies. The same four compounds impaired the growth of bloodstream Trypanosoma brucei brucei (EC₅₀ 1–8 μM) and two of them (compounds 6 and 14) showed a good selectivity index.     

Characterization of the Phytochemical Composition and Bioactivities of Anacyclus maroccanus Ball. and Anacyclus radiatus Loisel Aerial Parts: Preliminary Evidence for the Possible Development of Moroccan Plants

In the present study, the phytochemical composition and bioactivities of A. maroccanus (AM) and A. radiatus (AR), two ecotypes collected in the Demnate road and Essaouira regions, respectively, were studied to highlight a pharmacological interest and to enable possible pharmaceutical development. To this end, methanolic and ethyl acetate extracts were prepared for each ecotype by fractionation; next, their phytochemical composition was evaluated by spectrophotometric and chromatographic analysis. Moreover, in line with the available evidence for Anacyclus spp. and their traditional use, a screening of bioactivities, including antioxidant, hypoglycemic, antiglycative, chelating, and antibacterial activities, was performed. The extracts were characterized by high amounts of polyphenols, tannins, and flavonoids, especially in the methanolic extracts; these samples were also enriched in carotenoids despite a lower chlorophyll content. Chlorogenic acid and rutin were the major identified compounds. The extracts also showed interesting hypoglycemic, antiglycative, and antibacterial properties, although with differences in efficacy and potency. Present results provide more scientific basis to the ethnopharmacological uses of Anacyclus spp. and suggest a further interest in AM and AR ecotypes as natural sources of bioactive compounds and/or phytocomplexes for possible pharmaceutical and nutraceutical developments.     

A Comparative Analysis of Machine Learning Techniques for Muon Count in UHECR Extensive Air-Showers

The main goal of this work is to adapt a Physics problem to the Machine Learning (ML) domain and to compare several techniques to solve it. The problem consists of how to perform muon count from the signal registered by particle detectors which record a mix of electromagnetic and muonic signals. Finding a good solution could be a building block on future experiments. After proposing an approach to solve the problem, the experiments show a performance comparison of some popular ML models using two different hadronic models for the test data. The results show that the problem is suitable to be solved using ML as well as how critical the feature selection stage is regarding precision and model complexity.