Postdepositional Behavior of Molybdenum in Deep Sediments and Implications for Paleoredox Reconstruction

Molybdenum (Mo) is a trace element sensitive to oceanic redox conditions. The fidelity of sedimentary Mo as a paleoredox proxy of coeval seawater depends on the extent of Mo remobilization during postdepositional processes. Here we present the Mo content and isotope profiles for deep sediments from the Nankai Trough, Japan. The Mo signature suggests that these sediments have experienced extensive early diagenesis and hydrothermal alteration at depth. Iron (Fe)‐manganese (Mn) (oxyhydr)oxide alteration combined with Mo thiolation leads to a more than twenty‐fold enrichment of Mo within the sulfate reduction zone. Hydrothermal fluids and Mo adsorption onto Fe‐Mn (oxyhydr)oxides cause extremely negative Mo‐isotope values at the underthrust zone. These postdepositional Mo signals might be misinterpreted as expanded anoxia in the water column. Our findings highlight the importance of constraining postdepositional effects on Mo‐based proxies during paleoredox reconstruction

Iron fertilization–induced deoxygenation of eastern equatorial Pacific Ocean intermediate waters during the Paleocene–Eocene thermal maximum

The Paleocene–Eocene thermal maximum (PETM), a transient period of global warming, is considered to be an important analog for future greenhouse conditions. It was accompanied by a significant carbon cycle perturbation. Although ocean deoxygenation across the PETM is reported widely, its mechanism in the open ocean remains uncertain. Here, we present magnetic and geochemical analyses of sediments from the eastern equatorial Pacific Ocean. We found that iron fertilization during the PETM by eolian dust and volcanic eruptions fueled eastern equatorial Pacific Ocean productivity. This process led to increased organic matter degradation and oxygen consumption in intermediate waters, leading to deoxygenation. Our findings suggest that iron fertilization could be an important driver of open-ocean oxygen loss, as a side effect of global warming

A lytic phage to control multidrug-resistant avian pathogenic Escherichia coli (APEC) infection

The inappropriate use of antibiotics has led to the emergence of multidrug-resistant strains. Bacteriophages (phages) have gained renewed attention as promising alternatives or supplements to antibiotics. In this study, a lytic avian pathogenic Escherichia coli (APEC) phage designated as PEC9 was isolated and purified from chicken farm feces samples. The morphology, genomic information, optimal multiplicity of infection (MOI), one-step growth curve, thermal stability, pH stability, in vitro antibacterial ability and biofilm formation inhibition ability of the phage were determined. Subsequently, the therapeutic effects of the phages were investigated in the mice model. The results showed that PEC9 was a member of the siphovirus-like by electron microscopy observation. Biological characterization revealed that it could lyse two serotypes of E. coli, including O1 (9/20) and O2 (6/20). The optimal multiplicity of infection (MOI) of phage PEC9 was 0.1. Phage PEC9 had a latent period of 20 min and a burst period of 40 min, with an average burst size of 68 plaque-forming units (PFUs)/cell. It maintained good lytic activity at pH 3-11 and 4-50°C and could efficiently inhibit the bacterial planktonic cell growth and biofilm formation, and reduce bacterial counts within the biofilm, when the MOI was 0.01, 0.1, and 1, respectively. Whole-genome sequencing showed that PEC9 was a dsDNA virus with a genome of 44379 bp and GC content of 54.39%. The genome contains 56 putative ORFs and no toxin, virulence, or resistance-related genes were detected. Phylogenetic tree analysis showed that PEC9 is closely related to E. coli phages vB_EcoS_Zar3M, vB_EcoS_PTXU06, SECphi18, ZCEC10, and ZCEC11, but most of these phages exhibit different gene arrangement. The phage PEC9 could successfully protect mice against APEC infection, including improved survival rate, reduced bacterial loads, and organ lesions. To conclude, our results suggest that phage PEC9 may be a promising candidate that can be used as an alternative to antibiotics in the control of APEC infection

Towards Exascale Computation for Turbomachinery Flows

A state-of-the-art large eddy simulation code has been developed to solve compressible flows in turbomachinery. The code has been engineered with a high degree of scalability, enabling it to effectively leverage the many-core architecture of the new Sunway system. A consistent performance of 115.8 DP-PFLOPs has been achieved on a high-pressure turbine cascade consisting of over 1.69 billion mesh elements and 865 billion Degree of Freedoms (DOFs). By leveraging a high-order unstructured solver and its portability to large heterogeneous parallel systems, we have progressed towards solving the grand challenge problem outlined by NASA, which involves a time-dependent simulation of a complete engine, incorporating all the aerodynamic and heat transfer components.Comment: SC23, November, 2023, Denver, CO., US

A 3D study on the amplification of regional haze and particle growth by local emissions

The role of new particle formation (NPF) events and their contribution to haze formation through subsequent growth in polluted megacities is still controversial. To improve the understanding of the sources, meteorological conditions, and chemistry behind air pollution, we performed simultaneous measurements of aerosol composition and particle number size distributions at ground level and at 260 m in central Beijing, China, during a total of 4 months in 2015-2017. Our measurements show a pronounced decoupling of gas-to-particle conversion between the two heights, leading to different haze processes in terms of particle size distributions and chemical compositions. The development of haze was initiated by the growth of freshly formed particles at both heights, whereas the more severe haze at ground level was connected directly to local primary particles and gaseous precursors leading to higher particle growth rates. The particle growth creates a feedback loop, in which a further development of haze increases the atmospheric stability, which in turn strengthens the persisting apparent decoupling between the two heights and increases the severity of haze at ground level. Moreover, we complemented our field observations with model analyses, which suggest that the growth of NPF-originated particles accounted up to similar to 60% of the accumulation mode particles in the Beijing-Tianjin-Hebei area during haze conditions. The results suggest that a reduction in anthropogenic gaseous precursors, suppressing particle growth, is a critical step for alleviating haze although the number concentration of freshly formed particles (3-40 nm) via NPF does not reduce after emission controls.Peer reviewe

Patchouli Alcohol Modulates the Pregnancy X Receptor/Toll-like Receptor 4/Nuclear Factor Kappa B Axis to Suppress Osteoclastogenesis

The incidence of osteoporosis, which is primarily characterized by plethoric osteoclast (OC) formation and severe bone loss, has increased in recent years. Millions of people worldwide, especially postmenopausal women, suffer from osteoporosis. The drugs commonly used to treat osteoporosis still exist many disadvantages, but natural extracts provide options for the treatment of osteoporosis. Therefore, the identification of cost-effective natural compounds is important. Patchouli alcohol (PA), a natural compound extracted from Pogostemon cablin that exerts anti-inflammatory effects, is used as a treatment for gastroenteritis. However, no research on the use of Patchouli alcohol in osteoporosis has been reported. We found that PA dose-dependently inhibited the receptor activator of nuclear factor kappa-B ligand (RANKL)-induced formation and function of OCs without cytotoxicity. Furthermore, these inhibitory effects were reflected in the significant effect of PA on the NF-κB signaling pathway, as PA suppressed the transcription factors NFATc1 and c-Fos. We also determined that PA activated expression of the nuclear receptor pregnane X receptor (PXR) and promoted the PXR/Toll-like receptor 4 (TLR4) axis to inhibit the nuclear import of NF-κB (p50 and p65). Additionally, PA exerted therapeutic effects against osteoporosis in ovariectomized (OVX) mice, supporting the use of PA as a treatment for osteoporosis in the future

Construction of a cross-species cell landscape at single-cell level.

Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal-Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging

Estimating Aboveground Carbon Stock at the Scale of Individual Trees in Subtropical Forests Using UAV LiDAR and Hyperspectral Data

Accurate estimation of aboveground carbon stock for individual trees is important for evaluating forest carbon sequestration potential and maintaining ecosystem carbon balance. Airborne light detection and ranging (LiDAR) data has been widely used to estimate tree-level carbon stock. However, few studies have explored the potential of combining LiDAR and hyperspectral data to estimate tree-level carbon stock. The objective of this study is to explore the potential of integrating unmanned aerial vehicle (UAV) LiDAR with hyperspectral data for tree-level aboveground carbon stock estimation. To achieve this goal, we first delineated individual trees by a CHM-based watershed segmentation algorithm. We then extracted structural and spectral features from UAV LiDAR and hyperspectral data respectively. Then, Pearson correlation analysis was conducted to assess the correlation between LiDAR features, hyperspectral features, and tree-level carbon stock, based on which, features were selected for model development. Finally, we developed tree-level carbon stock estimation models based on the Schumacher–Hall formula and stepwise multiple regression. Results showed that both LiDAR and hyperspectral features were strongly correlated to tree-level carbon stock. Both tree height (H, r = 0.75) and Green index (GI, r = 0.83) had the highest correlation coefficients with tree-level carbon stock in LiDAR and hyperspectral features, respectively. The best model using LiDAR features alone includes the metrics of H, the 10th height percentile of points (PH10), and mean height of points (Hmean), and can explain 74% of the variations in tree-level carbon stock. Similarly, the best model using hyperspectral data includes GI and modified normalized differential vegetation index (mNDVI), and has similar explanatory power (r2 = 0.75). The model that integrates predictors, namely, GI and the 95th height percentile of points (PH95) from hyperspectral and LiDAR data, substantially improves the explanatory power (r2 = 0.89). These results indicated that while either LiDAR data or hyperspectral data alone can estimate tree-level carbon stock with reasonable accuracy, combining LiDAR and hyperspectral features can substantially improve the explanatory power of the model. Such results suggested that tree-level carbon stock estimation can greatly benefit from the complementary nature of LiDAR-detected structural characteristics and hyperspectral-captured spectral information of vegetation