Aminoacyl-tRNA Synthetases as Valuable Targets for Antimicrobial Drug Discovery

Aminoacyl-tRNA synthetases (aaRSs) catalyze the esterification of tRNA with a cognate amino acid and are essential enzymes in all three kingdoms of life. Due to their important role in the translation of the genetic code, aaRSs have been recognized as suitable targets for the development of small molecule anti-infectives. In this review, following a concise discussion of aaRS catalytic and proof-reading activities, the various inhibitory mechanisms of reported natural and synthetic aaRS inhibitors are discussed. Using the expanding repository of ligand-bound X-ray crystal structures, we classified these compounds based on their binding sites, focusing on their ability to compete with the association of one, or more of the canonical aaRS substrates. In parallel, we examined the determinants of species-selectivity and discuss potential resistance mechanisms of some of the inhibitor classes. Combined, this structural perspective highlights the opportunities for further exploration of the aaRS enzyme family as antimicrobial targets.     

Inhibition of Autophagy Does Not Re-Sensitize Acute Myeloid Leukemia Cells Resistant to Cytarabine

Elevated activation of the autophagy pathway is currently thought to be one of the survival mechanisms allowing therapy-resistant cancer cells to escape elimination, including for cytarabine (AraC)-resistant acute myeloid leukemia (AML) patients. Consequently, the use of autophagy inhibitors such as chloroquine (CQ) is being explored for the re-sensitization of AraC-resistant cells. In our study, no difference in the activity of the autophagy pathway was detected when comparing AraC-Res AML cell lines to parental AraC-sensitive AML cell lines. Furthermore, treatment with autophagy inhibitors CQ, 3-Methyladenine (3-MA), and bafilomycin A1 (BafA1) did not re-sensitize AraC-Res AML cell lines to AraC treatment. However, in parental AraC-sensitive AML cells, treatment with AraC did activate autophagy and, correspondingly, combination of AraC with autophagy inhibitors strongly reduced cell viability. Notably, the combination of these drugs also yielded the highest level of cell death in a panel of patient-derived AML samples even though not being additive. Furthermore, there was no difference in the cytotoxic effect of autophagy inhibition during AraC treatment in matched de novo and relapse samples with differential sensitivity to AraC. Thus, inhibition of autophagy may improve AraC efficacy in AML patients, but does not seem warranted for the treatment of AML patients that have relapsed with AraC-resistant disease.     

Oxidation State Modulation of Bismuth for Efficient Electrocatalytic Nitrogen Reduction to Ammonia

Electrocatalytic nitrogen reduction reaction (NRR) is a promising strategy for ammonia (NH₃) production under ambient conditions. However, it is severely impeded by the challenging activation of the NN bond and the competing hydrogen evolution reaction (HER), which makes it crucial to design electrocatalysts rationally for efficient NRR. Herein, the rational design of bismuth (Bi) nanoparticles with different oxidation states embedded in carbon nanosheets (Bi@C) as efficient NRR electrocatalysts is reported. The NRR performance of Bi@C improves with the increase of Bi⁰/Bi³⁺ atomic ratios, indicating that the oxidation state of Bi plays a significant role in electrochemical ammonia synthesis. As a result, the Bi@C nanosheets annealed at 900  ° C with the optimal oxidation state of Bi demonstrate the best NRR performance with a high NH₃ yield rate and remarkable Faradaic efficiency of 15.10  ± 0.43% at − 0.4 V versus RHE. Density functional theory calculations reveal that the effective modulation of the oxidation state of Bi can tune the p-filling of active Bi sites and strengthen adsorption of *NNH, which boost the potential-determining step and facilitate the electrocatalytic NRR under ambient conditions. This work may offer valuable insights into the rational material design by modulating oxidation states for efficient electrocatalysis.     

High-temperature oxidation behavior of monolithic Zr3[Al(Si)]4C6 and its composite incorporating 30vol% ZrB2-SiC: Providing a basis for broadening the service temperature

To provide a basis for the high-temperature oxidation of ultra-high temperature ceramics (UHTCs), the oxidation behavior of Zr₃[Al(Si)]₄C₆ and a novel Zr₃[Al(Si)]₄C₆-ZrB₂-SiC composite at 1500 °C were investigated for the first time. From the calculation results, the oxidation kinetics of the two specimens follow the oxidation dynamic parabolic law. Zr₃[Al(Si)]₄C₆ exhibited a thinner oxide scale and lower oxidation rate than those of the composite under the same conditions. The oxide scale of Zr₃[Al(Si)]₄C₆ exhibited a two-layer structure, while that of the composite exhibited a three-layer structure. Owing to the volatilization of B₂O₃ and the active oxidation of SiC, a porous oxide layer formed in the oxide scale of the composite, resulting in the degradation of its oxidation performance. Furthermore, the cracks and defects in the oxide scale of the composite indicate that the reliability of the oxide scale was poor. The results support the service temperature of the obtained ceramics.     

Controllable preparation of porous ZrB2–SiC ceramics via using KCl space holders

In this work, a novel and facile technique based on using KCl as space holders, along with partial sintering (at 1900 °C for 30 min), was explored to prepare porous ZrB₂–SiC ceramics with controllable pore structure, tunable compressive strength and thermal conductivity. The as-prepared porous ZrB₂–SiC samples possess high porosity of 45–67%, low average pore size of 3–7 μm, high compressive strength of 32–106 MPa, and low room temperature thermal conductivity of 13–34 W m⁻¹ K⁻¹. The porosity, pore structure, compressive strength and thermal conductivity of porous ZrB₂–SiC ceramics can be tuned simply by changing KCl content and its particle size. The effect of porosity and pore structure on the thermal conductivity of as-prepared porous ZrB₂–SiC ceramics was examined and found to be consistent with the classical model for porous materials. The poring mechanism of porous ZrB₂–SiC samples via adding pore-forming agent combined with partial sintering was also preliminary illustrated.     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Unipolar plasma electrolytic oxidation: Waveform optimisation for corrosion resistance of commercially pure titanium

This study deals with the anodisation of titanium grade 2 in 0.5-M sulphuric acid using a pulsed signal in a unipolar regime. The electrical parameters investigated are voltage, frequency and duty cycle. The use of duty cycles with a high percentage of anodic polarisation (90%), combined with high frequencies (1000 Hz) and the higher voltage tested (220 V), favoured the establishment of a plasma regime involving strong dielectric discharges, allowing the growth of thicker oxides but with rough architecture. The corrosion resistance of the formed film has been characterised by potentiodynamic tests in 0.5-M NaBr for localised corrosion resistance and by immersion tests in 10% v/v sulphuric acid solution for a uniform corrosion assessment. Current–time curves, visual observations and electron microscope analysis (scanning electron microscopy, energy-dispersive X-ray spectroscopy) were the tools selected to provide a correlation between technological parameters and oxide growth mechanism. For localised and uniform corrosion, anodisation at 220 V with a high level of anodic polarisation (90%) and frequency (1000 Hz) was verified to be particularly advantageous.     

YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.     

Catalytic combustion synthesis of CNTs/MgO composite powders and the influences on the thermal shock resistance of low-carbon Al2O3–C refractories

Using MgC₂O₄, Mg powders as raw materials and Ni(NO₃)₂?6H₂O as a catalyst, CNTs/MgO composite powders were prepared by a catalytic combustion synthesis method. The CNTs/MgO composite powders were characterized by XRD, Raman spectroscopy, FESEM/EDS and HRTEM. The effects of catalyst content on the degree of graphitization and aspect ratio of the CNTs in composite powders were investigated. Moreover, the thermal shock resistance of low-carbon Al₂O₃–C refractories after adding the composite powder was investigated. The results indicated that the CNTs prepared with 1 wt% Ni(NO₃)₂?6H₂O addition had a higher degree of graphitization and aspect ratio. In particular, the aspect ratio could reach approximately 200. The growth mechanism of hollow bamboo-like CNTs in the composite powders was proven to be a V-L-S mechanism. The thermal shock resistance of Al₂O₃–C samples could be improved significantly after adding CNTs/MgO composite powders. In particular, compared with CM0, the residual strength ratio of Al₂O₃–C samples with added 2.5 wt% composite powders could be increased 63.9%.     

Preparation of high-purity SiC ceramics with good plasma corrosion resistance by hot-pressing sintering

High-purity SiC ceramic devices are applied in semiconductor industry owing to their outstanding properties. Nevertheless, it is difficult to densify SiC ceramics without any sintering additive even by HP sintering. In this work, high-purity and dense SiC ceramics were fabricated by HP sintering with very low amounts of sintering aids. Residual B content was only 556 ppm and relative density was more than 99.5%. Furthermore, thermal conductivity of as-prepared SiC ceramics was improved from 155 W m^?1 K^?1 to 167 W m^?1 K^?1 by increasing holding time and their plasma corrosion resistance was promoted in the meantime. The as-prepared high-purity SiC ceramics have broad application prospects in the field of semiconductor industry.