αC including a novel three- component non-heme diiron monooxygenase system

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Polar Antiferromagnets Produced with Orbital-Order

Polar magnetic states are realized in pseudocubic manganite thin films fabricated on high-index substrates, in which a Jahn-Teller (JT) distortion remains an active variable. Several types of orbital-orders were found to develop large optical second harmonic generation, signaling broken-inversion-symmetry distinct from their bulk forms and films on (100) substrates. The observed symmetry-lifting and first-principles calculation both indicate that the modified JT q2 mode drives Mn-site off-centering upon orbital order, leading to the possible cooperation of "Mn-site polarization" and magnetism.Comment: 5 pages, 4 figure

Development of P450-BM3 using molecular dynamics simulations- A tribute to the late Professor Hideaki Yamada

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A three-component monooxygenase from Rhodococcus wratislaviensis may expand industrial applications of bacterial enzymes

地球外有機化合物に対する微生物代謝の解明から全く新規な酵素系を発見 --生命分子進化の理解や産業応用に期待--. 京都大学プレスリリース. 2021-01-20.The high-valent iron-oxo species formed in the non-heme diiron enzymes have high oxidative reactivity and catalyze difficult chemical reactions. Although the hydroxylation of inert methyl groups is an industrially promising reaction, utilizing non-heme diiron enzymes as such a biocatalyst has been difficult. Here we show a three-component monooxygenase system for the selective terminal hydroxylation of α-aminoisobutyric acid (Aib) into α-methyl-D-serine. It consists of the hydroxylase component, AibH1H2, and the electron transfer component. Aib hydroxylation is the initial step of Aib catabolism in Rhodococcus wratislaviensis C31-06, which has been fully elucidated through a proteome analysis. The crystal structure analysis revealed that AibH1H2 forms a heterotetramer of two amidohydrolase superfamily proteins, of which AibHm2 is a non-heme diiron protein and functions as a catalytic subunit. The Aib monooxygenase was demonstrated to be a promising biocatalyst that is suitable for bioprocesses in which the inert C–H bond in methyl groups need to be activated

A machine learning model for predicting the lymph node metastasis of early gastric cancer not meeting the endoscopic curability criteria

The version of record of this article, first published in Gastric Cancer, is available online at Publisher’s website: https://doi.org/10.1007/s10120-024-01511-8.Background: We developed a machine learning (ML) model to predict the risk of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) who did not meet the existing Japanese endoscopic curability criteria and compared its performance with that of the most common clinical risk scoring system, the eCura system. Methods: We used data from 4,042 consecutive patients with EGC from 21 institutions who underwent endoscopic submucosal dissection (ESD) and/or surgery between 2010 and 2021. All resected EGCs were histologically confirmed not to satisfy the current Japanese endoscopic curability criteria. Of all patients, 3,506 constituted the training cohort to develop the neural network-based ML model, and 536 constituted the validation cohort. The performance of our ML model, as measured by the area under the receiver operating characteristic curve (AUC), was compared with that of the eCura system in the validation cohort. Results: LNM rates were 14% (503/3,506) and 7% (39/536) in the training and validation cohorts, respectively. The ML model identified patients with LNM with an AUC of 0.83 (95% confidence interval, 0.76–0.89) in the validation cohort, while the eCura system identified patients with LNM with an AUC of 0.77 (95% confidence interval, 0.70–0.85) (P = 0.006, DeLong’s test). Conclusions: Our ML model performed better than the eCura system for predicting LNM risk in patients with EGC who did not meet the existing Japanese endoscopic curability criteria. Mini-abstract: We developed a neural network-based machine learning model that predicts the risk of lymph node metastasis in patients with early gastric cancer who did not meet the endoscopic curability criteria