High-valent metal-oxo moieties have been implicated as key intermediates preceding various oxidation processes. The critical O-O bond formation step in the Kok cycle that is presumed to generate molecular oxygen occurs through the high-valent Mn-oxo species of the water oxidation complex, i.e., the Mn4Ca cluster in photosystem II. Here, we report the spectroscopic characterization of new intermediates during the water oxidation reaction of manganese-based heterogeneous catalysts and assign them as low-spin Mn(IV)-oxo species. Recently, the effects of the spin state in transition metal catalysts on catalytic reactivity have been intensely studied; however, no detailed characterization of a low-spin Mn(IV)-oxo intermediate species currently exists. We demonstrate that a low-spin configuration of Mn(IV), S = 1/2, is stably present in a heterogeneous electrocatalyst of Ni-doped monodisperse 10-nm Mn3O4 nanoparticles via oxo-ligand field engineering. An unprecedented signal (g = 1.83) is found to evolve in the electron paramagnetic resonance spectrum during the stepwise transition from the Jahn-Teller-distorted Mn(III).  https://www.selleckchem.com/products/l-arginine-l-glutamate.html  In-situ Raman analysis directly provides the evidence for Mn(IV)-oxo species as the active intermediate species. Computational analysis confirmed that the substituted nickel species induces the formation of a z-axis-compressed octahedral C4v crystal field that stabilizes the low-spin Mn(IV)-oxo intermediates.An enduring geological mystery concerns the missing xenon problem, referring to the abnormally low concentration of xenon compared to other noble gases in Earth's atmosphere. Identifying mantle minerals that can capture and stabilize xenon has been a great challenge in materials physics and xenon chemistry. Here, using an advanced crystal structure search algorithm in conjunction with first-principles calculations we find reactions of xenon with recently discovered iron peroxide FeO2, forming robust xenon-iron oxides Xe2FeO2 and XeFe3O6 with significant Xe-O bonding in a wide range of pressure-temperature conditions corresponding to vast regions in Earth's lower mantle. Calculated mass density and sound velocities validate Xe-Fe oxides as viable lower-mantle constituents. Meanwhile, Fe oxides do not react with Kr, Ar and Ne. It means that if Xe exists in the lower mantle at the same pressures as FeO2, xenon-iron oxides are predicted as potential Xe hosts in Earth's lower mantle and could provide the repository for the atmosphere's missing Xe. These findings establish robust materials basis, formation mechanism, and geological viability of these Xe-Fe oxides, which advance fundamental knowledge for understanding xenon chemistry and physics mechanisms for the possible deep-Earth Xe reservoir.To understand how the RuvC catalytic domain of Class 2 Cas proteins cleaves DNA, it will be necessary to elucidate the structures of RuvC-containing Cas complexes in their catalytically competent states. Cas12i2 is a Class 2 type V-I CRISPR-Cas endonuclease that cleaves target dsDNA by an unknown mechanism. Here, we report structures of Cas12i2-crRNA-DNA complexes and a Cas12i2-crRNA complex. We reveal the mechanism of DNA recognition and cleavage by Cas12i2, and activation of the RuvC catalytic pocket induced by a conformational change of the Helical-II domain. The seed region (nucleotides 1-8) is dispensable for RuvC activation, but the duplex of the central spacer (nucleotides 9-15) is required. We captured the catalytic state of Cas12i2, with both metal ions and the ssDNA substrate bound in the RuvC catalytic pocket. Together, our studies provide significant insights into the DNA cleavage mechanism by RuvC-containing Cas proteins.Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ICIs. The choice of strategy is based on heterogeneous biomarkers that can dynamically change during therapy. Thus, there is a compelling need to identify comprehensive biomarkers that can be used longitudinally to help guide therapy choice. Herein, we report a 18F-FDG-PET/CT-based deep learning model, which demonstrates high accuracy in EGFR mutation status prediction across patient cohorts from different institutions. A deep learning score (EGFR-DLS) was significantly and positively associated with longer progression free survival (PFS) in patients treated with EGFR-TKIs, while EGFR-DLS is significantly and negatively associated with higher durable clinical benefit, reduced hyperprogression, and longer PFS among patients treated with ICIs. Thus, the EGFR-DLS provides a non-invasive method for precise quantification of EGFR mutation status in NSCLC patients, which is promising to identify NSCLC patients sensitive to EGFR-TKI or ICI-treatments.New storage technologies are needed to keep up with the global demands of data generation. DNA is an ideal storage medium due to its stability, information density and ease-of-readout with advanced sequencing techniques. However, progress in writing DNA is stifled by the continued reliance on chemical synthesis methods. The enzymatic synthesis of DNA is a promising alternative, but thus far has not been well demonstrated in a parallelized manner. Here, we report a multiplexed enzymatic DNA synthesis method using maskless photolithography. Rapid uncaging of Co2+ ions by patterned UV light activates Terminal deoxynucleotidyl Transferase (TdT) for spatially-selective synthesis on an array surface. Spontaneous quenching of reactions by the diffusion of excess caging molecules confines synthesis to light patterns and controls the extension length. We show that our multiplexed synthesis method can be used to store digital data by encoding 12 unique DNA oligonucleotide sequences with video game music, which is equivalent to 84 trits or 110 bits of data.Accurately characterizing land surface changes with Earth Observation requires geo-located ground truth. In the European Union (EU), a tri-annual surveyed sample of land cover and land use has been collected since 2006 under the Land Use/Cover Area frame Survey (LUCAS). A total of 1351293 observations at 651780 unique locations for 106 variables along with 5.4 million photos were collected during five LUCAS surveys. Until now, these data have never been harmonised into one database, limiting full exploitation of the information. This paper describes the LUCAS point sampling/surveying methodology, including collection of standard variables such as land cover, environmental parameters, and full resolution landscape and point photos, and then describes the harmonisation process. The resulting harmonised database is the most comprehensive in-situ dataset on land cover and use in the EU. The database is valuable for geo-spatial and statistical analysis of land use and land cover change. Furthermore, its potential to provide multi-temporal in-situ data will be enhanced by recent computational advances such as deep learning.