Subtype-specific 3D genome alteration in acute myeloid leukaemia.

Acute myeloid leukaemia (AML) represents a set of heterogeneous myeloid malignancies, and hallmarks include mutations in epigenetic modifiers, transcription factors and kinases1-5. The extent to which mutations in AML drive alterations in chromatin 3D structure and contribute to myeloid transformation is unclear. Here we use Hi-C and whole-genome sequencing to analyse 25 samples from patients with AML and 7 samples from healthy donors. Recurrent and subtype-specific alterations in A/B compartments, topologically associating domains and chromatin loops were identified. RNA sequencing, ATAC with sequencing and CUT&Tag for CTCF, H3K27ac and H3K27me3 in the same AML samples also revealed extensive and recurrent AML-specific promoter-enhancer and promoter-silencer loops. We validated the role of repressive loops on their target genes by CRISPR deletion and interference. Structural variation-induced enhancer-hijacking and silencer-hijacking events were further identified in AML samples. Hijacked enhancers play a part in AML cell growth, as demonstrated by CRISPR screening, whereas hijacked silencers have a downregulating role, as evidenced by CRISPR-interference-mediated de-repression. Finally, whole-genome bisulfite sequencing of 20 AML and normal samples revealed the delicate relationship between DNA methylation, CTCF binding and 3D genome structure. Treatment of AML cells with a DNA hypomethylating agent and triple knockdown of DNMT1, DNMT3A and DNMT3B enabled the manipulation of DNA methylation to revert 3D genome organization and gene expression. Overall, this study provides a resource for leukaemia studies and highlights the role of repressive loops and hijacked cis elements in human diseases.

Producing fast and active Rubisco in tobacco to enhance photosynthesis.

Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) performs most of the carbon fixation on Earth. However, plant Rubisco is an intrinsically inefficient enzyme given its low carboxylation rate, representing a major limitation to photosynthesis. Replacing endogenous plant Rubisco with a faster Rubisco is anticipated to enhance crop photosynthesis and productivity. However, the requirement of chaperones for Rubisco expression and assembly has obstructed the efficient production of functional foreign Rubisco in chloroplasts. Here, we report the engineering of a Form 1A Rubisco from the proteobacterium Halothiobacillus neapolitanus in Escherichia coli and tobacco (Nicotiana tabacum) chloroplasts without any cognate chaperones. The native tobacco gene encoding Rubisco large subunit was genetically replaced with H. neapolitanus Rubisco (HnRubisco) large and small subunit genes. We show that HnRubisco subunits can form functional L8S8 hexadecamers in tobacco chloroplasts at high efficiency, accounting for ∼40% of the wild-type tobacco Rubisco content. The chloroplast-expressed HnRubisco displayed a ∼2-fold greater carboxylation rate and supported a similar autotrophic growth rate of transgenic plants to that of wild-type in air supplemented with 1% CO2. This study represents a step toward the engineering of a fast and highly active Rubisco in chloroplasts to improve crop photosynthesis and growth.

Bioproduction of cerium-bearing magnetite and application to improve carbon-black supported platinum catalysts.

BACKGROUND: Biogeochemical processing of metals including the fabrication of novel nanomaterials from metal contaminated waste streams by microbial cells is an area of intense interest in the environmental sciences. RESULTS: Here we focus on the fate of Ce during the microbial reduction of a suite of Ce-bearing ferrihydrites with between 0.2 and 4.2 mol% Ce. Cerium K-edge X-ray absorption near edge structure (XANES) analyses showed that trivalent and tetravalent cerium co-existed, with a higher proportion of tetravalent cerium observed with increasing Ce-bearing of the ferrihydrite. The subsurface metal-reducing bacterium Geobacter sulfurreducens was used to bioreduce Ce-bearing ferrihydrite, and with 0.2 mol% and 0.5 mol% Ce, an Fe(II)-bearing mineral, magnetite (Fe(II)(III)2O4), formed alongside a small amount of goethite (FeOOH). At higher Ce-doping (1.4 mol% and 4.2 mol%) Fe(III) bioreduction was inhibited and goethite dominated the final products. During microbial Fe(III) reduction Ce was not released to solution, suggesting Ce remained associated with the Fe minerals during redox cycling, even at high Ce loadings. In addition, Fe L2,3 X-ray magnetic circular dichroism (XMCD) analyses suggested that Ce partially incorporated into the Fe(III) crystallographic sites in the magnetite. The use of Ce-bearing biomagnetite prepared in this study was tested for hydrogen fuel cell catalyst applications. Platinum/carbon black electrodes were fabricated, containing 10% biomagnetite with 0.2 mol% Ce in the catalyst. The addition of bioreduced Ce-magnetite improved the electrode durability when compared to a normal Pt/CB catalyst. CONCLUSION: Different concentrations of Ce can inhibit the bioreduction of Fe(III) minerals, resulting in the formation of different bioreduction products. Bioprocessing of Fe-minerals to form Ce-containing magnetite (potentially from waste sources) offers a sustainable route to the production of fuel cell catalysts with improved performance.

Negative impact of maternal depressive symptoms on infancy neurodevelopment: a moderated mediation effect of maternal inflammation.

Maternal depression promotes maternal inflammation and the risk of neurodevelopmental disorder in offspring, but the role of inflammation on the association between depression and neurodevelopment in offspring has not been extensively studied in humans. This study aims to examine the mediating role of maternal inflammation on the relationship between maternal depression and neurodevelopment in infants. 146 mother-child pairs were identified from Tianjin Maternal and Child Health Education and Service Cohort (Tianjin MCHESC). Maternal depression was investigated by the Center for Epidemiologic Studies Depression Scale and the Edinburgh Postnatal Depression Scale, and depressive trajectories were identified by latent class growth analysis. Inflammatory biomarkers in the three trimesters were assessed with enzyme-linked immunoassay. The Children Neuropsychological and Behavior Scale-Revision 2016 was used to measure neurodevelopment in infants. Principal component analysis was performed to identify inflammatory condition. Stepwise multiple linear regression analysis and mediation analysis were used to identify association among maternal depression, maternal inflammation and neurodevelopment in infants. Offspring in the low and moderate maternal depression groups exhibited higher adaptive behavior development quotient than those in the high maternal depression group. Higher maternal c-reactive protein level and higher inflammatory level in acute-phase of inflammation in the first trimester, and moderate maternal depression were associated with lower adaptive behavior quotients of infants. Inflammatory level in acute-phase of inflammation in the first trimester significantly mediated the association between maternal depression and adaptive behavior development of infants, with explaining 11.85% of the association. Maternal depression could impair adaptive behavior development in infants by inflammation.

A Review of Dynamic Object Filtering in SLAM Based on 3D LiDAR.

SLAM (Simultaneous Localization and Mapping) based on 3D LiDAR (Laser Detection and Ranging) is an expanding field of research with numerous applications in the areas of autonomous driving, mobile robotics, and UAVs (Unmanned Aerial Vehicles). However, in most real-world scenarios, dynamic objects can negatively impact the accuracy and robustness of SLAM. In recent years, the challenge of achieving optimal SLAM performance in dynamic environments has led to the emergence of various research efforts, but there has been relatively little relevant review. This work delves into the development process and current state of SLAM based on 3D LiDAR in dynamic environments. After analyzing the necessity and importance of filtering dynamic objects in SLAM, this paper is developed from two dimensions. At the solution-oriented level, mainstream methods of filtering dynamic targets in 3D point cloud are introduced in detail, such as the ray-tracing-based approach, the visibility-based approach, the segmentation-based approach, and others. Then, at the problem-oriented level, this paper classifies dynamic objects and summarizes the corresponding processing strategies for different categories in the SLAM framework, such as online real-time filtering, post-processing after the mapping, and Long-term SLAM. Finally, the development trends and research directions of dynamic object filtering in SLAM based on 3D LiDAR are discussed and predicted.

Numerical Investigation on the Influence of Turbine Rotor Parameters on the Eddy Current Sensor for the Dynamic Blade Tip Clearance Measurement.

Eddy current sensors are increasingly being used to measure the dynamic blade tip clearance in turbines due to their robust anti-interference capabilities and non-contact measurement advantages. However, the current research primarily focuses on enhancing the performance of eddy current sensors themselves, with few studies investigating the influence of turbine rotor parameters on the measurements taken by these sensors for dynamic blade tip clearance. Hence, this paper addresses this gap by using COMSOL Multiphysics 6.2 software to establish a finite model with circuit interfaces. Additionally, the model's validity was verified through experiments. This model is used to simulate the voltage output of the sensor and the measurement of dynamic blade tip clearance under various rotor parameters. The results indicate that the length and number of blades, as well as the hub radius, significantly affect the sensor voltage output in comparison to rotation speed. Furthermore, we show that traditional static calibration methods are inadequate for measuring dynamic blade tip clearance using eddy current sensors. Instead, it is demonstrated that incorporating rotor parameters into the calibration of eddy current sensors can enhance the accuracy of dynamic blade tip clearance measurements.

Experimental Investigation on the Effect of Coil Shape on Planar Eddy Current Sensor Characteristic for Blade Tip Clearance.

Given the increasing application of eddy current sensors for measuring turbine tip clearance in aero engines, enhancing the performance of these sensors is essential for improving measurement accuracy. This study investigates the influence of coil shape on the measurement performance of planar eddy current sensors and identifies an optimal coil shape to enhance sensing capabilities. To achieve this, various coil shapes-specifically circular, square, rectangular wave, and triangular wave-were designed and fabricated, featuring different numbers of turns for the experiment at room temperature. By employing a method for calculating coil inductance, the performance of each sensor was evaluated based on key metrics: measurement range, sensitivity, and linearity. Experimental results reveal that the square coil configuration outperforms other shapes in overall measurement performance. Notably, the square coil demonstrated a measurement range of 0 mm to 8 mm, a sensitivity of 0.115685 µH/mm, and an impressive linearity of 98.41% within the range of 0 mm to 2 mm. These findings indicate that the square coil configuration enhances measurement capabilities. The conclusions drawn from this study provide valuable insights for selecting coil shapes and optimizing the performance of planar eddy current sensors, thereby contributing to the advancement of turbine tip clearance measurement techniques in aero engines.

Mechanistic insights into temperature-driven retention and speciation changes of heavy metals (HMs) in ash residues from Co-combustion of refuse-derived fuel (RDF) and red mud.

Red mud is a promising candidate for promoting the incineration of Refuse Derived Fuel (RDF) and stabilizing the resulting incineration ash. The combustion conditions, notably temperature, significantly steers the migration and transformation of harmful metal components during combustion, and ultimately affect their retention and speciation in the ash residue. The study attempted to investigate the effect of co-combustion temperature on the enrichment and stability of Cr, Ni, Cu, Zn, Cd and Pb within bottom ashes, and to reveal the underlined promotion mechanism of red mud addition. As temperature increased, red mud's active components formed a robust matrix, helping the formation, melting, and vitrification of silicates and aluminosilicates in the bottom ashes. The process significantly contributed to the encapsulation and stabilization of heavy metals such as Ni, Cu, Zn, Cd, and Pb, with their residual fractions ascending to 71.37%, 55.75%, 74.78%, 84.24%, and 93.54%, respectively. Conversely, high temperatures led to an increase in the proportion of Cr in the extremely unstable acid-soluble fraction of the bottom ashes, reaching 31.52%, posing a heightened risk of environmental migration. Considering the stability of heavy metals in the bottom ashes and the combustion characteristics, 800 °C is identified as the optimal temperature for the co-combustion of RDF and red mud, balancing efficiency and environmental safety. The findings will provide valuable insights for the co-utilization strategy of RDF and red mud, contributing to more informed decision-making in waste-to-energy processes.

Constructing an Ultra-Rapid Nanoconfinement-Enhanced Fluorescence Clinical Detection Platform by Using Machine Learning and Tunable DNA Xerogel "Probe".

Low mass transfer efficiency and unavoidable matrix effects seriously limit the development of rapid and accurate determination of biosensing systems. Herein, we have successfully constructed an ultra-rapid nanoconfinement-enhanced fluorescence clinical detection platform based on machine learning (ML) and DNA xerogel "probe", which was performed by detecting neutrophil gelatinase-associated lipocalin (NGAL, protein biomarker of acute kidney injury). By regulating pore sizes of the xerogels, the transfer of NGAL in xerogels can approximate that in homogeneous solution. Due to electrostatic attraction of the pore entrances, NGAL rapidly enriches on the surface and inside the xerogels. The reaction rate of NGAL and aptamer cross-linked in xerogels is also accelerated because of the nanoconfinement effect-induced increasing reactant concentration and the enhanced affinity constant KD between reactants, which can be promoted by ∼667-fold than that in bulk solution, thus achieving ultra-rapid detection (ca. 5 min) of human urine. The platform could realize one-step detection without sample pretreatments due to the antiligand exchange effect on the surface of N-doped carbon quantum dots (N-CQDs) in xerogels, in which ligand exchange between -COOH and underlying interfering ions in urine will be inhibited due to higher adsorption energy of -COOH on the N-CQD surface relative to the interfering ions. Based on the ML-extended program, the real-time analysis of the urine fluorescence spectra can be completed within 2 s. Interestingly, by changing DNA, aptamer sequences, or xerogel fluorescence intensities, the detection platform can be customized for targeted diseases.

Thermalbibacter longus gen. nov., sp. nov., isolated from a hot spring.

An isolate, designated CFH 74404T, was recovered from a hot spring in Tengchong, Yunnan province, PR China. Phylogenetic analysis indicated that the isolate belongs to the family Thermomicrobiaceae and showed the highest 16S rRNA gene sequence similarity to Thermorudis peleae KI4T (93.6 %), Thermorudis pharmacophila WKT50.2T (93.1 %), Thermomicrobium roseum DSM 5159T (92.0 %) and Thermomicrobium carboxidum KI3T (91.7 %). The average amino acid identity and average nucleotide identity values between strain CFH 74404T and the closest relatives were 42.0-75.9 % and 67.0-77.3 %, respectively. Cells of strain CFH 74404T stained Gram-positive and were aerobic, non-motile and short rod-shaped. Growth occurred at 20-65 °C (optimum, 55 °C), pH 6.0-8.0 (optimum, pH 7.0) and with up to 2.0 % (w/v) NaCl (optimum 0-1.0 %, w/v). The predominant respiratory quinone was MK-8. The major fatty acids (>10 %) were C18 : 0 (50.8 %) and C20 : 0 (16.8 %). The polar lipid profile of strain CFH 74404T included diphosphatidylglycerol, four unidentified phosphoglycolipids, phosphatidylinositol and three unidentified glycolipids. The G+C content of the genomic DNA was determined to be 67.1 mol% based on the draft genome sequence. On the basis of phenotypic, phylogenetic and genotypic analyses, it is concluded that strain CFH 74404T represents a new species of a novel genus Thermalbibacter of the family Thermomicrobiaceae, for which the name Thermalbibacter longus gen. nov., sp. nov. is proposed. The type strain is CFH 74404T (=KCTC 62930T=CGMCC 1.61585T).