Search for: All records

We apply the barred Schwarzschild method developed by Tahmasebzadeh et al. (2022) to a barred S0 galaxy, NGC 4371, observed by IFU instruments from the TIMER and ATLAS3D projects. We construct the gravitational potential by combining a fixed black hole mass, a spherical dark matter halo, and stellar mass distribution deprojected from 3.6 μm S$^4$G image considering an axisymmetric disc and a triaxial bar. We independently modelled kinematic data from TIMER and ATLAS3D. Both models fit the data remarkably well. We find a consistent bar pattern speed from the two sets of models with $\Omega _{\rm p} = 23.6 \pm 2.8 \, \mathrm{km \, s^{-1} \, kpc^{-1} }$ and $\Omega _{\rm p} = 22.4 \pm 3.5 \, \mathrm{km \, s^{-1} \, kpc^{-1} }$, respectively. The dimensionless bar rotation parameter is determined to be $\mathcal {R} \equiv R_{\rm cor}/R_{\rm bar}=1.88 \pm 0.37$, indicating a likely slow bar in NGC 4371. Additionally, our model predicts a high amount of dark matter within the bar region ($M_{\rm DM}/ M_{\rm total}$$\sim 0.51 \pm 0.06$), which, aligned with the predictions of cosmological simulations, indicates that fast bars are generally found in baryon-dominated discs. Based on the best-fitting model, we further decompose the galaxy into multiple 3D orbital structures, including a BP/X bar, a classical bulge, a nuclear disc, and a main disc. The BP/X bar is not perfectly included in the input 3D density model, but BP/X-supporting orbits are picked through the fitting to the kinematic data. This is the first time a real barred galaxy has been modelled utilizing the Schwarzschild method including a 3D bar.

 

Due to the scarcity of C–F bond-forming enzymatic reactions in nature and the contrasting prevalence of organofluorine moieties in bioactive compounds, developing biocatalytic fluorination reactions represents a pre-eminent challenge in enzymology, biocatalysis and synthetic biology. Additionally, catalytic enantioselective C(sp3)–H fluorination remains a challenging problem facing synthetic chemists. Although many non-haem iron halogenases have been discovered to promote C(sp3)–H halogenation reactions, efforts to convert these iron halogenases to fluorinases have remained unsuccessful. Here we report the development of an enantioselective C(sp3)–H fluorination reaction, catalysed by a plant-derived non-haem enzyme 1-aminocyclopropane-1-carboxylic acid oxidase (ACCO), which is repurposed for radical rebound fluorination. Directed evolution afforded a C(sp3)–H fluorinating enzyme ACCOCHF displaying 200-fold higher activity, substantially improved chemoselectivity and excellent enantioselectivity, converting a range of substrates into enantioenriched organofluorine products. Notably, almost all the beneficial mutations were found to be distal to the iron centre, underscoring the importance of substrate tunnel engineering in non-haem iron biocatalysis. Computational studies reveal that the radical rebound step with the Fe(III)–F intermediate has a low activation barrier of 3.4 kcal mol−1 and is kinetically facile. 

This work revisits a publication by Beanet al.(2018) that reports seven amino acid substitutions are essential for the evolution ofl‐DOPA 4,5‐dioxygenase (DODA) activity in Caryophyllales. In this study, we explore several concerns which led us to replicate the analyses of Beanet al.(2018).

Our comparative analyses, with structural modelling, implicate numerous residues additional to those identified by Beanet al.(2018), with many of these additional residues occurring around the active site of BvDODAα1. We therefore replicated the analyses of Beanet al.(2018) to re‐observe the effect of their original seven residue substitutions in a BvDODAα2 background, that is the BvDODAα2‐mut3 variant.

Multiplein vivoassays, in bothSaccharomyces cerevisiaeandNicotiana benthamiana, did not result in visible DODA activity in BvDODAα2‐mut3, with betalain production always 10‐fold below BvDODAα1.In vitroassays also revealed substantial differences in both catalytic activity and pH optima between BvDODAα1, BvDODAα2 and BvDODAα2‐mut3 proteins, explaining their differing performancein vivo.

In summary, we were unable to replicate thein vivoanalyses of Beanet al.(2018), and our quantitativein vivoandin vitroanalyses suggest a minimal effect of these seven residues in altering catalytic activity of BvDODAα2. We conclude that the evolutionary pathway to high DODA activity is substantially more complex than implied by Beanet al.(2018).

 

Catalytic asymmetric α-alkylation of carbonyl compounds represents a long-standing challenge in synthetic organic chemistry. Herein, we advance a dual biocatalytic platform for the efficient asymmetric alkylation of α-keto acids. First, guided by our recently obtained crystal structures, we develop SgvM^VAVas a general biocatalyst for the enantioselective methylation, ethylation, allylation and propargylation of a range of α-keto acids with total turnover numbers (TTNs) up to 4,600. Second, we mine a family of bacterial HMTs fromPseudomonasspecies sharing less than 50% sequence identities with known HMTs and evaluated their activities in SAM regeneration. Our best performing HMT fromP. aeruginosa,PaHMT, displays the highest SAM regeneration efficiencies (TTN up to 7,700) among HMTs characterized to date. Together, the synergistic use of SgvM^VAVandPaHMT affords a fully biocatalytic protocol for asymmetric methylation featuring a record turnover efficiency, providing a solution to the notorious problem of asymmetric alkylation.

 

It has been widely suggested in literature that a lithium fluoride (LiF)-rich solid electrolyte interphase (SEI) affects Coulombic efficiency (CE) of the Li metal anode used with liquid electrolytes. Yet, the influence of LiF on Li metal deposition has been challenging to examine. Herein, we developed a method to synthesize LiF nanoscale particles with tunable sizes (30–300 nm) on Cu electrodes by electrochemical reduction of fluorinated gases under controlled discharge rates and capacities. The impact of LiF nanoparticles on overpotential and morphology of Li deposition was further studied in a conventional carbonate electrolyte. By cyclic voltammetry, Li plating overpotentials exhibit a clear correlation with the total surface area of LiF particles. Additionally, Li metal deposits (10μAh cm⁻²) nucleated under galvanostatic conditions (0.5 mA cm⁻²) on Cu/LiF showed increasing feature sizes with a lower average LiF particle size and higher coverage of LiF. However, no significant improvement in CE was observed for LiF-coated Cu. Our findings provide evidence that a particle-based mode of SEI fluorination can influence early-stage Li nucleation to a modest degree, and this effect is maximized when LiF is uniformly and densely distributed. However, sparser and larger LiF have vanishing or even detrimental effect on cycling performance.

 

Collaborative localization is an essential capability for a team of robots such as connected vehicles to collaboratively estimate object locations from multiple perspectives with reliant cooperation. To enable collaborative localization, four key challenges must be addressed, including modeling complex relationships between observed objects, fusing observations from an arbitrary number of collaborating robots, quantifying localization uncertainty, and addressing latency of robot communications. In this paper, we introduce a novel approach that integrates uncertainty-aware spatiotemporal graph learning and model-based state estimation for a team of robots to collaboratively localize objects. Specifically, we introduce a new uncertainty-aware graph learning model that learns spatiotemporal graphs to represent historical motions of the objects observed by each robot over time and provides uncertainties in object localization. Moreover, we propose a novel method for integrated learning and model-based state estimation, which fuses asynchronous observations obtained from an arbitrary number of robots for collaborative localization. We evaluate our approach in two collaborative object localization scenarios in simulations and on real robots. Experimental results show that our approach outperforms previous methods and achieves state-of-the-art performance on asynchronous collaborative localization.