Angioid Streaks throughout Pseudoxanthoma Elasticum

A venomous snakebite is an emergency. However, antivenoms are rare and very similar, difficult to produce and preserve, and almost impossible to be used for emergency treatment. Therefore, it would be of great significance to develop convenient, efficient and broad-spectrum snake venom neutralizing nano-materials. In this study, inspired by boiled eggs, a new concept based on a ZnO complex (ZC) for the treatment of snake venoms is proposed. In vitro and in vivo experiments proved that ZC could widely adsorb biological (including snake) venoms and effectively reduce the concentration of toxic protein in the blood. More importantly, ZC could realize photothermal conversion under the stimulation of near-infrared (NIR) irradiation, resulting in protein hydrolyzation of venoms, thereby fundamentally prolonging survival time. In addition, ZC not only showed good biocompatibility, but also could inhibit bacterial reproduction, alleviate inflammation, and contribute to the healing of open wounds caused by biological venoms.Graphitic carbon nitride (g-C3N4) is recognized as a favorable substrate for monoatom catalysts due to its uniform nanoholes for anchoring metal monoatoms, while the oxygen evolution reaction (OER) overpotential (ηOER) values of g-C3N4-based metal monoatom catalysts are still large. To reduce the ηOER values, a class of novel TM1NM1NM1/g-C3N4 was designed via density functional theory simulations, where TM1 = Fe1, Co1 or Ni1 and NM1 = C1, N1 or O1. Contributing by two extra-NM1 atoms, the OER catalytic activities of these materials were effectively improved owing to the shortened TM1-NM bonds and weakened chemical activity of TM1 atoms. Based on the volcano activity relationship between the theoretical overpotential (ηOER) and d band center of the TM1 atom (εd), the chemical activity of TM1 atoms needs to be adjusted to a suitable magnitude (εd near -4.883 eV) for a good catalytic activity. The designed Fe1C1O1/g-C3N4 with the εd of -4.893 eV exhibited an excellent OER catalytic activity of ηOER = 0.219 V. This strategy was applied to devise the reaction active sites and highly efficient catalysts by adjusting the chemical activity of the TM1 atom with suitable extra-NM1 atoms.Magnetic double deflection experiments reveal that nuclear spins diminish electron spin coherence in isolated AlSn12 clusters. A temperature-dependent fraction of the endohedral cage clusters show superatomic response in Stern-Gerlach experiments which allows one to detect spin flips under controlled conditions in a double deflection arrangement. The concentration of nuclear spins in the tin cage is varied by using isotopically enriched tin samples. Hyperfine interaction, nuclear spin statistics and spin dynamics are discussed in detail. It is demonstrated that state-interference in the multistate Landau-Zener system AlSn12 explains why the spin decoherence is significantly increased when one or two nuclear spins are already present in the cluster, while the spin coherence no longer changes significantly with the addition of further nuclear spins.To render the sodium ion battery (SIB) competitive among other technologies, the processes behind sodium storage in hard carbon anodes must be understood. For this purpose, electrochemical impedance spectroscopy (EIS) is usually undervalued, since fitting the spectra with equivalent circuit models requires an a priori knowledge about the system at hand. The analysis of the distribution of relaxation times (DRT) is an alternative, which refrains from fitting arbitrarily nested equivalent circuits. In this paper, the sodiation and desodiation of a hard carbon anode is studied by EIS at different states of charge (SOC). By reconstructing the DRT function, highly resolved information on the number and relative contribution of individual electrochemical processes is derived. During the sloping part of the sodiation curve, mass transport is found to be the most dominant source of resistance but rapidly diminishes when the plateau phase is reached. An equivalent circuit model qualitatively reproducing the experimental data of the sloping region was built upon the DRT results, which is particularly useful for future EIS studies on hard carbon SIB anodes. More importantly, this work contributes to establish EIS as a practical tool to directly study electrode processes without the bias of a previously assumed model.The growing demand for self-powered devices has led to the study of novel energy storage solutions that exploit green energies whilst ensuring self-sufficiency. In this context, doped metal oxide nanocrystals (MO NCs) are interesting nanosized candidates with the potential to unify solar energy conversion and storage into one set of materials. In this review, we aim to present recent and important developments of doped MO NCs for light-driven multi-charge accumulation (i.e., photodoping) and solar energy storage. We will discuss the general concept of photodoping, the spectroscopic and theoretical tools to determine the charging process, together with unresolved open questions. Temsirolimus molecular weight We conclude the review by highlighting possible device architectures based on doped MO NCs that are expected to considerably impact the field of energy storage by combining in a unique way the conversion and storage of solar power and opening the path towards competitive and novel light-driven energy storage solutions.We report a non-antibody GLUT1 inhibitor probe NBDQ that is 30 times more sensitive than the traditional GLUT1 transportable tracer for cancer cell imaging and Warburg effect-based tumor detection. NBDQ reveals significant advantages in terms of tumor selectivity, fluorescence stability and in vivo biocompatibility in xenograft tumor imaging, including triple-negative breast cancer.Different theoretical mechanisms have been proposed for explaining complex social phenomena. For example, explanations for observed trends in population alcohol use have been postulated based on norm theory, role theory, and others. Many mechanism-based models of phenomena attempt to translate a single theory into a simulation model. However, single theories often only represent a partial explanation for the phenomenon. The potential of integrating theories together, computationally, represents a promising way of improving the explanatory capability of generative social science. This paper presents a framework for such integrative model discovery, based on multi-objective grammar-based genetic programming (MOGGP). The framework is demonstrated using two separate theory-driven models of alcohol use dynamics based on norm theory and role theory. The proposed integration considers how the sequence of decisions to consume the next drink in a drinking occasion may be influenced by factors from the different theories.