Electron filling and proton loss in radiation belts and SAA during 2018 storm based on ZH-1 satellite observations

<p>Based on data from the ZH-1 satellites, companied with Van Allen Probes and NOAA observations, we analyze the high energy particle evolutions in radiation belts, slot region and SAA during August 2018 major geomagnetic storm (minimum Dst ≈ −190 nT). </p><p>  1) Relativistic electron enhancements in extremely low L-shell regions (reaching L ∼ 3) were observed during storm. Contrary to what occurs in the outer belt, such an intense and deep electron penetration event is rare and more interesting. Strong whistler-mode (chorus and hiss) waves, with amplitudes 81–126 pT, were also observed in the extremely low L-shell simultaneously (reaching L ∼ 2.5) where the plasmapause was suppressed. The bounce-averaged diffusion coefficient calculations support that the chorus waves can play a significantly important role in diffusing and accelerating the 1–3 MeV electrons even in such low L-shells during storms.</p><p>2) A robust evidence is clearly demonstrated that the energetic electron flux with energy 30∼600 keV are increased by 2∼3 times in the inner radiation belt near equator and SAA region on dayside during the major geomagnetic storm. This is the first time that the 100s keV electron flux enhancement is reported to be potentially induced by the interaction with magnetosonic waves in extremely low L-shells (L<2) observed by Van Allen Probes. Proton loss in outer boundary of inner radiation belt takes place in energy of 2~220 MeV extensively during the occurrence of this storm but the loss mechanism is energy dependence which is consistent with some previous studies. It is confirmed that the magnetic field line curvature scattering plays a significant role in the proton loss phenomenon in energy 30-100 MeV during this storm. This work provides a beneficial help to comprehensively understand the charged particles trapping and loss in SAA region and inner radiation belt dynamic physics.</p>

On the Reactivity of mRNA Caps: C-H Oxidative Addition of 7-Methylguanosine to Pt(0)

<p>7-methylguanosine, the so-called mRNA cap 0 bears a very labile C8-H bond, due to the formation of an ylide/N-heterocyclic carbene, upon proton loss. The reaction of 7-methylguanosine with Pt(PPh3)4, via C-H oxidative addition, yields a hydrido–PtII carbene complex and this reactivity can be extrapolated to 7,9-dimethylguanine. </p>

On the Reactivity of mRNA Caps: C-H Oxidative Addition of 7-Methylguanosine to Pt(0)

<p>7-methylguanosine, the so-called mRNA cap 0 bears a very labile C8-H bond, due to the formation of an ylide/N-heterocyclic carbene, upon proton loss. The reaction of 7-methylguanosine with Pt(PPh3)4, via C-H oxidative addition, yields a hydrido–PtII carbene complex and this reactivity can be extrapolated to 7,9-dimethylguanine. </p>

Non-Linear Quantitative Structure–Activity Relationships Modelling, Mechanistic Study and In-Silico Design of Flavonoids as Potent Antioxidants

In this work, we developed quantitative structure–activity relationships (QSAR) models for prediction of oxygen radical absorbance capacity (ORAC) of flavonoids. Both linear (partial least squares—PLS) and non-linear models (artificial neural networks—ANNs) were built using parameters of two well-established antioxidant activity mechanisms, namely, the hydrogen atom transfer (HAT) mechanism defined with the minimum bond dissociation enthalpy, and the sequential proton-loss electron transfer (SPLET) mechanism defined with proton affinity and electron transfer enthalpy. Due to pronounced solvent effects within the ORAC assay, the hydration energy was also considered. The four-parameter PLS-QSAR model yielded relatively high root mean square errors (RMSECV = 0.783, RMSEE = 0.668, RMSEP = 0.900). Conversely, the ANN-QSAR model yielded considerably lower errors (RMSEE = 0.180 ± 0.059, RMSEP1 = 0.164 ± 0.128, and RMSEP2 = 0.151 ± 0.114) due to the inherent non-linear relationships between molecular structures of flavonoids and ORAC values. Five-fold cross-validation was found to be unsuitable for the internal validation of the ANN-QSAR model with a high RMSECV of 0.999 ± 0.253; which is due to limited sample size where resampling with replacement is a considerably better alternative. Chemical domains of applicability were defined for both models confirming their reliability and robustness. Based on the PLS coefficients and partial derivatives, both models were interpreted in terms of the HAT and SPLET mechanisms. Theoretical computations based on density functional theory at ωb97XD/6-311++G(d,p) level of theory were also carried out to further shed light on the plausible mechanism of anti-peroxy radical activity. Calculated energetics for simplified models (genistein and quercetin) with peroxyl radical derived from 2,2′-azobis (2-amidino-propane) dihydrochloride suggested that both SPLET and single electron transfer followed by proton loss (SETPL) mechanisms are competitive and more favorable than HAT in aqueous medium. The finding is in good accord with the ANN-based QSAR modelling results. Finally, the strongly predictive ANN-QSAR model was used to predict antioxidant activities for a series of 115 flavonoids designed combinatorially with flavone as a template. Structural trends were analyzed, and general guidelines for synthesis of new flavonoid derivatives with potentially potent antioxidant activities were given.