Uptake of zinc from the soil to the wheat grain: Nonlinear process prediction based on artificial neural network and geochemical data.

Trace elements in plants primarily derive from soils, subsequently influencing human health through the food chain. Therefore, it is essential to understand the relationship of trace elements between plants and soils. Since trace elements from soils absorbed by plants is a nonlinear process, traditional multiple linear regression (MLR) models failed to provide accurate predictions. Zinc (Zn) was chosen as the objective element in this case. Using soil geochemical data, artificial neural networks (ANN) were utilized to develop predictive models that accurately estimated Zn content within wheat grains. A total of 4036 topsoil samples and 73 paired rhizosphere soil-wheat samples were collected for the simulation study. Through Pearson correlation analysis, the total content of elements (TCEs) of Fe, Mn, Zn, and P, as well as the available content of elements (ACEs) of B, Mo, N, and Fe, were significantly correlated with the Zn bioaccumulation factor (BAF). Upon comparison, ANN models outperformed MLR models in terms of prediction accuracy. Notably, the predictive performance using ACEs as input factors was better than that using TCEs. To improve the accuracy, a two-step model was established through multiple testing. Firstly, ACEs in the soil were predicted using TCEs and properties of the rhizosphere soil as input factors. Secondly, the Zn BAF in grains was predicted using ACE as input factors. Consequently, the content of Zn in wheat grains corresponding to 4036 topsoil samples was predicted. Results showed that 85.69 % of the land was suitable for cultivating Zn-rich wheat. This finding offers a more accurate method to predict the uptake of trace elements from soils to grains, which helps to warn about abnormal levels in grains and prevent potential health risks.

Identification of a Hippocampus-to-Zona Incerta Projection involved in Motor Learning.

Motor learning (ML), which plays a fundamental role in growth and physical rehabilitation, involves different stages of learning and memory processes through different brain regions. However, the neural mechanisms that underlie ML are not sufficiently understood. Here, a previously unreported neuronal projection from the dorsal hippocampus (dHPC) to the zona incerta (ZI) involved in the regulation of ML behaviors is identified. Using recombinant adeno-associated virus, the projections to the ZI are surprisingly identified as originating from the dorsal dentate gyrus (DG) and CA1 subregions of the dHPC. Furthermore, projection-specific chemogenetic and optogenetic manipulation reveals that the projections from the dorsal CA1 to the ZI play key roles in the acquisition and consolidation of ML behaviors, whereas the projections from the dorsal DG to the ZI mediate the retrieval/retention of ML behaviors. The results reveal new projections from the dorsal DG and dorsal CA1 to the ZI involved in the regulation of ML and provide insight into the stages over which this regulation occurs.

Batch and Continuous-Flow Electrochemical Geminal Difluorination of Indeno[1,2-c]furans.

An electrochemical gem-difluorination of indeno[1,2-c]furans using commercially available and easy-to-use triethylamine trihydrofluoride as both the electrolyte and fluorinating agent was developed. Remarkably, different reaction pathways of indeno[1,2-c]furans, i.e., paired electrolysis and net oxidation, are operative in a batch reactor and a continuous-flow microreactor to afford the corresponding gem-difluorinated indanones and indenones, respectively.

A Bibliometric Analysis of the Spatial Transcriptomics Literature from 2006 to 2023.

In recent years, spatial transcriptomics (ST) research has become a popular field of study and has shown great potential in medicine. However, there are few bibliometric analyses in this field. Thus, in this study, we aimed to find and analyze the frontiers and trends of this medical research field based on the available literature. A computerized search was applied to the WoSCC (Web of Science Core Collection) Database for literature published from 2006 to 2023. Complete records of all literature and cited references were extracted and screened. The bibliometric analysis and visualization were performed using CiteSpace, VOSviewer, Bibliometrix R Package software, and Scimago Graphica. A total of 1467 papers and reviews were included. The analysis revealed that the ST publication and citation results have shown a rapid upward trend over the last 3 years. Nature Communications and Nature were the most productive and most co-cited journals, respectively. In the comprehensive global collaborative network, the United States is the country with the most organizations and publications, followed closely by China and the United Kingdom. The author Joakim Lundeberg published the most cited paper, while Patrik L. Ståhl ranked first among co-cited authors. The hot topics in ST are tissue recognition, cancer, heterogeneity, immunotherapy, differentiation, and models. ST technologies have greatly contributed to in-depth research in medical fields such as oncology and neuroscience, opening up new possibilities for the diagnosis and treatment of diseases. Moreover, artificial intelligence and big data drive additional development in ST fields.

Altered nucleocytoplasmic export of adenosine-rich circRNAs by PABPC1 contributes to neuronal function.

Circular RNAs (circRNAs) are upregulated during neurogenesis. Where and how circRNAs are localized and what roles they play during this process have remained elusive. Comparing the nuclear and cytoplasmic circRNAs between H9 cells and H9-derived forebrain (FB) neurons, we identify that a subset of adenosine (A)-rich circRNAs are restricted in H9 nuclei but exported to cytosols upon differentiation. Such a subcellular relocation of circRNAs is modulated by the poly(A)-binding protein PABPC1. In the H9 nucleus, newly produced (A)-rich circRNAs are bound by PABPC1 and trapped by the nuclear basket protein TPR to prevent their export. Modulating (A)-rich motifs in circRNAs alters their subcellular localization, and introducing (A)-rich circRNAs in H9 cytosols results in mRNA translation suppression. Moreover, decreased nuclear PABPC1 upon neuronal differentiation enables the export of (A)-rich circRNAs, including circRTN4(2,3), which is required for neurite outgrowth. These findings uncover subcellular localization features of circRNAs, linking their processing and function during neurogenesis.

Regulation of intracellular process by two-component systems: Exploring the mechanism of plasmid-mediated conjugative transfer.

Plasmid-mediated conjugative transfer facilitates the dissemination of antibiotic resistance, yet the comprehensive regulatory mechanisms governing this process remain elusive. Herein, we established pure bacteria and activated sludge conjugation system to investigate the regulatory mechanisms of conjugative transfer, leveraging metformin as an exogenous agent. Transcriptomic analysis unveiled that substantial upregulation of genes associated with the two-component system (e.g., AcrB/AcrA, EnvZ/Omp, and CpxA/CpxR) upon exposure to metformin. Furthermore, downstream regulators of the two-component system, including reactive oxygen species (ROS), cytoplasmic membrane permeability, and adenosine triphosphate (ATP) production, were enhanced by 1.7, 1.4 and 1.1 times, respectively, compared to the control group under 0.1 mg/L metformin exposure. Moreover, flow sorting and high-throughput sequencing revealed increased microbial community diversity among transconjugants in activated sludge systems. Notably, the antibacterial potential of human pathogenic bacteria (e.g., Bacteroides, Escherichia-Shigella, and Lactobacillus) was augmented, posing a potential threat to human health. Our findings shed light on the spread of antibiotic resistance bacteria and assess the ecological risks associated with plasmid-mediated conjugative transfer in wastewater treatment systems.

Characterizing Spatially Continuous Variations in Tissue Microenvironment through Niche Trajectory Analysis.

Recent technological developments have made it possible to map the spatial organization of a tissue at the single-cell resolution. However, computational methods for analyzing spatially continuous variations in tissue microenvironment are still lacking. Here we present ONTraC as a strategy that constructs niche trajectories using a graph neural network-based modeling framework. Our benchmark analysis shows that ONTraC performs more favorably than existing methods for reconstructing spatial trajectories. Applications of ONTraC to public spatial transcriptomics datasets successfully recapitulated the underlying anatomical structure, and further enabled detection of tissue microenvironment-dependent changes in gene regulatory networks and cell-cell interaction activities during embryonic development. Taken together, ONTraC provides a useful and generally applicable tool for the systematic characterization of the structural and functional organization of tissue microenvironments.

Assessing the impact of mining on cyclic and linear methylsiloxane distribution in Tibetan soils: Source contribution and transport pattern.

The pervasive presence of methylsiloxanes (MSs), comprising linear and cyclic congeners, in the environment poses significant ecological risks, yet the understanding of their transport mechanisms and deposition patterns remains limited. This study analyzed the concentrations of 12 linear-MSs (L3-L14) and 7 cyclic-MSs (D3-D9) in 29 surface soil samples collected across varying altitudes (3726 to 4863 m) near the Jiama mining sector in Tibet, aiming to investigate the distribution and transport dynamics of MSs from the emission source. The distribution of total MS concentration (ranging from 50.1 to 593 ng/g) showed a remarkable correlation with proximity to the mining site, suggesting the emergent source of mining activities for the MSs in the remote environment of the Tibetan Plateau. Employing the innovative model of robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), the analysis predicted that the mining operations contributing 57.1 % of the total soil MSs, would significantly surpass contributions from traffic emissions (14.7 %), residential activities (13.2 %), and the environmental factor of total organic matter content (14.9 %). The Boltzmann equation effectively modeled the distribution pattern of soil MSs, highlighting atmospheric transport and gravitational settling as key distribution mechanisms. However, linear-MSs exhibited longer transport distances than cyclic-MSs and were more profoundly affected by prevailing wind directions, suggesting their differential environmental behaviors and risks. Our study underscored that the mining sector possibly emerged as a significant source of Tibetan MSs, and provided insights into the transport and fate of MSs in remote, high-altitude environments. The findings emphasize the need for targeted pollution control strategies to mitigate the environmental footprint of mining activities in Tibet and similar regions.

Analysis of nearly 3000 archaeal genomes from terrestrial geothermal springs sheds light on interconnected biogeochemical processes.

Terrestrial geothermal springs are physicochemically diverse and host abundant populations of Archaea. However, the diversity, functionality, and geological influences of these Archaea are not well understood. Here we explore the genomic diversity of Archaea in 152 metagenomes from 48 geothermal springs in Tengchong, China, collected from 2016 to 2021. Our dataset is comprised of 2949 archaeal metagenome-assembled genomes spanning 12 phyla and 392 newly identified species, which increases the known species diversity of Archaea by ~48.6%. The structures and potential functions of the archaeal communities are strongly influenced by temperature and pH, with high-temperature acidic and alkaline springs favoring archaeal abundance over Bacteria. Genome-resolved metagenomics and metatranscriptomics provide insights into the potential ecological niches of these Archaea and their potential roles in carbon, sulfur, nitrogen, and hydrogen metabolism. Furthermore, our findings illustrate the interplay of competition and cooperation among Archaea in biogeochemical cycles, possibly arising from overlapping functional niches and metabolic handoffs. Taken together, our study expands the genomic diversity of Archaea inhabiting geothermal springs and provides a foundation for more incisive study of biogeochemical processes mediated by Archaea in geothermal ecosystems.

Overlooked in-situ sulfur disproportionation fuels dissimilatory nitrate reduction to ammonium in sulfur-based system: Novel insight of nitrogen recovery.

Sulfur-based denitrification is a promising technology in treatments of nitrate-contaminated wastewaters. However, due to weak bioavailability and electron-donating capability of elemental sulfur, its sulfur-to-nitrate ratio has long been low, limiting the support for dissimilatory nitrate reduction to ammonium (DNRA) process. Using a long-term sulfur-packed reactor, we demonstrate here for the first time that DNRA in sulfur-based system is not negligible, but rather contributes a remarkable 40.5 %-61.1 % of the total nitrate biotransformation for ammonium production. Through combination of kinetic experiments, electron flow analysis, 16S rRNA amplicon, and microbial network succession, we unveil a cryptic in-situ sulfur disproportionation (SDP) process which significantly facilitates DNRA via enhancing mass transfer and multiplying 86.7-210.9 % of bioavailable electrons. Metagenome assembly and single-copy gene phylogenetic analysis elucidate the abundant genomes, including uc_VadinHA17, PHOS-HE36, JALNZU01, Thiobacillus, and Rubrivivax, harboring complete genes for ammonification. Notably, a unique group of self-SDP-coupled DNRA microorganism was identified. This study unravels a previously concealed fate of DNRA, which highlights the tremendous potential for ammonium recovery and greenhouse gas mitigation. Discovery of a new coupling between nitrogen and sulfur cycles underscores great revision needs of sulfur-driven denitrification technology.

Orthogonal multimodality integration and clustering in single-cell data.

Multimodal integration combines information from different sources or modalities to gain a more comprehensive understanding of a phenomenon. The challenges in multi-omics data analysis lie in the complexity, high dimensionality, and heterogeneity of the data, which demands sophisticated computational tools and visualization methods for proper interpretation and visualization of multi-omics data. In this paper, we propose a novel method, termed Orthogonal Multimodality Integration and Clustering (OMIC), for analyzing CITE-seq. Our approach enables researchers to integrate multiple sources of information while accounting for the dependence among them. We demonstrate the effectiveness of our approach using CITE-seq data sets for cell clustering. Our results show that our approach outperforms existing methods in terms of accuracy, computational efficiency, and interpretability. We conclude that our proposed OMIC method provides a powerful tool for multimodal data analysis that greatly improves the feasibility and reliability of integrated data.

Recent advances in mesenchymal stem cell therapy for myocardial infarction.

Myocardial infarction refers to the ischemic necrosis of myocardium, characterized by a sharp reduction or interruption of blood flow in the coronary arteries due to the coronary artery occlusion, resulting in severe and prolonged ischemia in the corresponding myocardium and ultimately leading to ischemic necrosis of the myocardium. Given its high risk, it is considered as one of the most serious health threats today. In current clinical practice, multiple approaches have been explored to diminish myocardial oxygen consumption and alleviate symptoms, but notable success remains elusive. Accumulated clinical evidence has showed that the implantation of mesenchymal stem cell for treating myocardial infarction is both effective and safe. Nevertheless, there persists controversy and variability regarding the standardizing MSC transplantation protocols, optimizing dosage, and determining the most effective routes of administration. Addressing these remaining issues will pave the way of integration of MSCs as a feasible mainstream cardiac treatment.

Characterization of a pangolin SARS-CoV-2-related virus isolate that uses the human ACE2 receptor.

Various SARS-CoV-2-related coronaviruses have been increasingly identified in pangolins, showing a potential threat to humans. Here we report the infectivity and pathogenicity of the SARS-CoV-2-related virus, PCoV-GX/P2V, which was isolated from a Malayan pangolin (Manis javanica). PCoV-GX/P2V could grow in human hepatoma, colorectal adenocarcinoma cells, and human primary nasal epithelial cells. It replicated more efficiently in cells expressing human angiotensin-converting enzyme 2 (hACE2) as SARS-CoV-2 did. After intranasal inoculation to the hACE2-transgenic mice, PCoV-GX/P2V not only replicated in nasal turbinate and lungs, but also caused interstitial pneumonia, characterized by infiltration of mixed inflammatory cells and multifocal alveolar hemorrhage. Existing population immunity established by SARS-CoV-2 infection and vaccination may not protect people from PCoV-GX/P2V infection. These findings further verify the hACE2 utility of PCoV-GX/P2V by in vivo experiments using authentic viruses and highlight the importance for intensive surveillance to prevent possible cross-species transmission.

CD4+CD25+ regulatory T cells ex vivo generated from autologous naïve CD4+ T cells suppress EAE progression.

CD4+CD25+ regulatory T cells (Tregs) play an important role in maintaining immune homeostasis in multiple sclerosis (MS). Hence, we aimed to explore the therapeutic efficacy and safety of adoptive cell therapy (ACT) utilizing induced antigen-specific Tregs in an animal model of MS, that is, in an experimental autoimmune encephalomyelitis (EAE) model. B cells from EAE model that were activated with soluble CD40L were used as antigen-presenting cells (APCs) to induce the differentiation of antigen-specific Tregs from naïve CD4 precursors, and then, a stepwise isolation of CD4+CD25highCD127low Tregs was performed using a flow sorter. All EAE mice were divided into Treg-treated group (2 × 104 cells in 0.2 mL per mouse, n = 14) and sham-treated group (0.2 mL normal saline (NS), n = 20), which were observed daily for clinical assessment, and for abnormal appearance for 6 weeks. Afterward, histological analysis, immunofluorescence and real-time PCR were performed. Compared to sham-treated mice, Treg-treated mice exhibited a significant decrease in disease severity scores and reduced inflammatory infiltration and demyelination in the spinal cord. Additionally, Tregs-treated mice demonstrated higher CCN3 protein and mRNA levels than sham-treated mice. The results of this preclinical study further support the therapeutic potential of this ACT approach in the treatment of MS.

Isolation and characterization of a pangolin-borne HKU4-related coronavirus that potentially infects human-DPP4-transgenic mice.

We recently detected a HKU4-related coronavirus in subgenus Merbecovirus (named pangolin-CoV-HKU4-P251T) from a Malayan pangolin1. Here we report isolation and characterization of pangolin-CoV-HKU4-P251T, the genome sequence of which is closest to that of a coronavirus from the greater bamboo bat (Tylonycteris robustula) in Yunnan Province, China, with a 94.3% nucleotide identity. Pangolin-CoV-HKU4-P251T is able to infect human cell lines, and replicates more efficiently in cells that express human-dipeptidyl-peptidase-4 (hDPP4)-expressing and pangolin-DPP4-expressing cells than in bat-DPP4-expressing cells. After intranasal inoculation with pangolin-CoV-HKU4-P251, hDPP4-transgenic female mice are likely infected, showing persistent viral RNA copy numbers in the lungs. Progressive interstitial pneumonia developed in the infected mice, characterized by the accumulation of macrophages, and increase of antiviral cytokines, proinflammatory cytokines, and chemokines in lung tissues. These findings suggest that the pangolin-borne HKU4-related coronavirus has a potential for emerging as a human pathogen by using hDPP4.

Temperature, pH, and oxygen availability contributed to the functional differentiation of ancient Nitrososphaeria.

Ammonia-oxidizing Nitrososphaeria are among the most abundant archaea on Earth and have profound impacts on the biogeochemical cycles of carbon and nitrogen. In contrast to these well-studied ammonia-oxidizing archaea (AOA), deep-branching non-AOA within this class remain poorly characterized because of a low number of genome representatives. Here, we reconstructed 128 Nitrososphaeria metagenome-assembled genomes from acid mine drainage and hot spring sediment metagenomes. Comparative genomics revealed that extant non-AOA are functionally diverse, with capacity for carbon fixation, carbon monoxide oxidation, methanogenesis, and respiratory pathways including oxygen, nitrate, sulfur, or sulfate, as potential terminal electron acceptors. Despite their diverse anaerobic pathways, evolutionary history inference suggested that the common ancestor of Nitrososphaeria was likely an aerobic thermophile. We further surmise that the functional differentiation of Nitrososphaeria was primarily shaped by oxygen, pH, and temperature, with the acquisition of pathways for carbon, nitrogen, and sulfur metabolism. Our study provides a more holistic and less biased understanding of the diversity, ecology, and deep evolution of the globally abundant Nitrososphaeria.

Enhanced OER catalytic activity of single metal atoms supported by the pentagonal NiN2 monolayer: insight from density functional theory calculations.

Two-dimensional material-supported single metal atom catalysts have been extensively studied and proved effective in electrocatalytic reactions in recent years. In this work, we systematically investigate the OER catalytic properties of single metal atoms supported by the NiN2 monolayer. Several typical transition metals with high single atom catalytic activity, such as Fe, Co, Ru, Rh, Pd, Ir, and Pt, were selected as catalytic active sites. The energy calculations show that transition metal atoms (Fe, Co, Ru, Rh, Pd, Ir, and Pt) are easily embedded in the NiN2 monolayer with Ni vacancies due to the negative binding energy. The calculated OER overpotentials of Fe, Co, Ru, Rh, Pd, Ir and Pt embedded NiN2 monolayers are 0.92 V, 0.47 V, 1.13 V, 0.66 V, 1.25 V, 0.28 V, and 0.94 V, respectively. Compared to the 0.57 V OER overpotential of typical OER noble metal catalysts IrO2, Co@NiN2 and Ir@NiN2 exhibit high OER catalytic activity due to lower overpotential, especially for Ir@NiN2. The high catalytic activity of the Ir embedded NiN2 monolayer can be explained well by the d-band center model. It is found that the adsorption strength of the embedded TM atoms with intermediates follows a linear relationship with their d-band centers. Besides, the overpotential of the Ir embedded NiN2 monolayer can be further reduced to 0.24 V under -2% biaxial strain. Such findings are expected to be employed in more two-dimensional material-supported single metal atom catalyzed reactions.

Matrin3 mediates differentiation through stabilizing chromatin loop-domain interactions and YY1 mediated enhancer-promoter interactions.

Although emerging evidence indicates that alterations in proteins within nuclear compartments elicit changes in chromosomal architecture and differentiation, the underlying mechanisms are not well understood. Here we investigate the direct role of the abundant nuclear complex protein Matrin3 (Matr3) in chromatin architecture and development in the context of myogenesis. Using an acute targeted protein degradation platform (dTAG-Matr3), we reveal the dynamics of development-related chromatin reorganization. High-throughput chromosome conformation capture (Hi-C) experiments revealed substantial chromatin loop rearrangements soon after Matr3 depletion. Notably, YY1 binding was detected, accompanied by the emergence of novel YY1-mediated enhancer-promoter loops, which occurred concurrently with changes in histone modifications and chromatin-level binding patterns. Changes in chromatin occupancy by Matr3 also correlated with these alterations. Overall, our results suggest that Matr3 mediates differentiation through stabilizing chromatin accessibility and chromatin loop-domain interactions, and highlight a conserved and direct role for Matr3 in maintenance of chromosomal architecture.

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data.

Cell-cell interaction (CCI) plays a pivotal role in cellular communication within the tissue microenvironment. The recent development of spatial transcriptomics (ST) technology and associated data analysis methods has empowered researchers to systematically investigate CCI. However, existing methods are tailored to single-cell resolution datasets, whereas the majority of ST platforms lack such resolution. Additionally, the detection of CCI through association screening based on ST data, which has complicated dependence structure, necessitates proper control of false discovery rates due to the multiple hypothesis testing issue in high dimensional spaces. To address these challenges, we introduce RECCIPE, a novel method designed for identifying cell signaling interactions across multiple cell types in spatial transcriptomic data. RECCIPE integrates gene expression data, spatial information and cell type composition in a multivariate regression framework, enabling genome-wide screening for changes in gene expression levels attributed to CCIs. We show that RECCIPE not only achieves high accuracy in simulated datasets but also provides new biological insights from real data obtained from a mouse model of Alzheimer's disease (AD). Overall, our framework provides a useful tool for studying impact of cell-cell interactions on gene expression in multicellular systems.